Intelligent digital assistant in a multi-tasking environment

Information

  • Patent Grant
  • 12175977
  • Patent Number
    12,175,977
  • Date Filed
    Wednesday, April 19, 2023
    a year ago
  • Date Issued
    Tuesday, December 24, 2024
    10 days ago
Abstract
Systems and processes for operating a digital assistant are provided. In one example, a method includes receiving a first speech input from a user. The method further includes identifying context information and determining a user intent based on the first speech input and the context information. The method further includes determining whether the user intent is to perform a task using a searching process or an object managing process. The searching process is configured to search data, and the object managing process is configured to manage objects. The method further includes, in accordance with a determination the user intent is to perform the task using the searching process, performing the task using the searching process; and in accordance with the determination that the user intent is to perform the task using the object managing process, performing the task using the object managing process.
Description
FIELD

The present disclosure relates generally to a digital assistant and, more specifically, to a digital assistant that interacts with a user to perform a task in a multi-tasking environment.


BACKGROUND

Digital assistants are increasing popular. In a desktop or tablet environment, a user frequently multi-tasks including searching files or information, managing files or folders, playing movies or songs, editing documents, adjusting system configurations, sending emails, etc. It is often cumbersome and inconvenient for the user to manually perform multiple tasks in parallel and to frequently switch between tasks. It is thus desirable for a digital assistant to have the ability to assist the user to perform some of the tasks in a multi-tasking environment based on a user's voice input.


BRIEF SUMMARY

Some existing techniques for assisting the user to perform a task in a multi-tasking environment may include, for example, dictation. Typically, a user may be required to manually perform many other tasks in a multi-tasking environment. As an example, a user may have been working on a presentation yesterday on his or her desktop computer and may wish to continue to work on the presentation. The user is typically required to manually locate the presentation on his or her desktop computer, open the presentation, and continue the editing of the presentation.


As another example, a user may have been booking a flight on his or her smartphone when the user is away from his desktop computer. The user may wish to continue booking the flight when the desktop computer is available. In existing technologies, the user needs to launch a web browser and start over on the flight booking process at the user's desktop computer. In other words, the prior flight booking progress that the user made at the smartphone may not be continued at the user's desktop computer.


As another example, a user may be editing a document on his or her desktop computer and wish to change a system configuration such as changing the brightness level of the screen, turning on Bluetooth connections, or the like. In existing technologies, the user may need to stop editing the document, find and launch the brightness configuration application, and manually change the settings. In a multi-tasking environment, some existing technologies are incapable of performing tasks as described in the above examples based on a user's speech input. Providing a voice-enabled digital assistant in a multi-tasking environment is thus desired and advantageous.


Systems and processes for operating a digital assistant are provided. In accordance with one or more examples, a method includes, at a user device with one or more processors and memory, receiving a first speech input from a user. The method further includes identifying context information associated with the user device and determining a user intent based on the first speech input and the context information. The method further includes determining whether the user intent is to perform a task using a searching process or an object managing process. The searching process is configured to search data stored internally or externally to the user device, and the object managing process is configured to manage objects associated with the user device. The method further includes, in accordance with a determination that the user intent is to perform the task using the searching process, performing the task using the searching process. The method further includes, in accordance with the determination that the user intent is to perform the task using the object managing process, performing the task using the object managing process.


In accordance with one or more examples, a method includes, at a user device with one or more processors and memory, receiving a speech input from a user to perform a task. The method further includes identifying context information associated with the user device and determining a user intent based on the speech input and context information associated with the user device. The method further includes, in accordance with user intent, determining whether the task is to be performed at the user device or at a first electronic device communicatively connected to the user device. The method further includes, in accordance with a determination that the task is to be performed at the user device and content for performing the task is located remotely, receiving the content for performing the task. The method further includes, in accordance with a determination that the task is to be performed at the first electronic device and the content for performing the task is located remotely to the first electronic device, providing the content for performing the task to the first electronic device.


In accordance with one or more examples, a method includes, at a user device with one or more processors and memory, receiving a speech input from a user to manage one or more system configurations of the user device. The user device is configured to concurrently provide a plurality of user interfaces. The method further includes identifying context information associated with the user device and determining a user intent based on the speech input and context information. The method further includes determining whether the user intent indicates an informational request or a request for performing a task. The method further includes, in accordance with a determination that the user intent indicates an informational request, providing a spoken response to the informational request. The method further includes, in accordance with a determination that the user intent indicates a request for performing a task, instantiating a process associated with the user device to perform the task.


Executable instructions for performing these functions are, optionally, included in a non-transitory computer-readable storage medium or other computer program product configured for execution by one or more processors. Executable instructions for performing these functions are, optionally, included in a transitory computer-readable storage medium or other computer program product configured for execution by one or more processors.





BRIEF DESCRIPTION OF THE DRAWINGS

For a better understanding of the various described embodiments, reference should be made to the Detailed Description below, in conjunction with the following drawings in which like reference numerals refer to corresponding parts throughout the figures.



FIG. 1 is a block diagram illustrating a system and environment for implementing a digital assistant according to various examples.



FIG. 2A is a block diagram illustrating a portable multifunction device implementing the client-side portion of a digital assistant in accordance with some embodiments.



FIG. 2B is a block diagram illustrating exemplary components for event handling according to various examples.



FIG. 3 illustrates a portable multifunction device implementing the client-side portion of a digital assistant according to various examples.



FIG. 4 is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface according to various examples.



FIG. 5A illustrates an exemplary user interface for a menu of applications on a portable multifunction device according to various examples.



FIG. 5B illustrates an exemplary user interface for a multifunction device with a touch-sensitive surface that is separate from the display according to various examples.



FIG. 6A illustrates a personal electronic device according to various examples.



FIG. 6B is a block diagram illustrating a personal electronic device according to various examples.



FIG. 7A is a block diagram illustrating a digital assistant system or a server portion thereof according to various examples.



FIG. 7B illustrates the functions of the digital assistant shown in FIG. 7A according to various examples.



FIG. 7C illustrates a portion of an ontology according to various examples.



FIGS. 8A-8F illustrate functionalities of performing a task using a search process or an object managing process by a digital assistant according to various examples.



FIGS. 9A-9H illustrate functionalities of performing a task using a search process by a digital assistant according to various examples.



FIGS. 10A-10B illustrate functionalities of performing a task using an object managing process by a digital assistant according to various examples.



FIGS. 11A-11D illustrate functionalities of performing a task using a search process by a digital assistant according to various examples.



FIGS. 12A-12D illustrate functionalities of performing a task using a search process or an object managing process by a digital assistant according to various examples.



FIGS. 13A-13C illustrate functionalities of performing a task using an object managing process by a digital assistant according to various examples.



FIGS. 14A-14D illustrate functionalities of performing a task at a user device using remotely located content by a digital assistant according to various examples.



FIGS. 15A-15D illustrate functionalities of performing a task at a first electronic device using remotely located content by a digital assistant according to various examples.



FIGS. 16A-16C illustrate functionalities of performing a task at a first electronic device using remotely located content by a digital assistant according to various examples.



FIGS. 17A-17E illustrate functionalities of performing a task at a user device using remotely located content by a digital assistant according to various examples.



FIGS. 18A-18F illustrate functionalities of providing system configuration information in response to an informational request of the user by a digital assistant according to various examples.



FIGS. 19A-19D illustrate functionalities of performing a task in response to a user request by a digital assistant according to various examples.



FIGS. 20A-20G illustrate a flow diagram of an exemplary process for operating a digital assistant according to various examples.



FIGS. 21A-21E illustrate a flow diagram of an exemplary process for operating a digital assistant according to various examples.



FIGS. 22A-22D illustrate a flow diagram of an exemplary process for operating a digital assistant according to various examples.



FIG. 23 illustrates a block diagram of an electronic device according to various examples.





DETAILED DESCRIPTION

In the following description of the disclosure and embodiments, reference is made to the accompanying drawings, in which it is shown by way of illustration, of specific embodiments that can be practiced. It is to be understood that other embodiments and examples can be practiced and changes can be made without departing from the scope of the disclosure.


Techniques for providing a digital assistant in a multi-tasking environment are desirable. As described herein, techniques for providing a digital assistant in a multi-tasking environment are desired for various purposes such as reducing the cumbersomeness of searching objects or information, enabling efficient object management, maintaining continuity between tasks performed at the user device and at another electronic device, and reducing the user's manual effort in adjusting system configurations. Such techniques are advantageous by allowing the user to operate a digital assistant to perform various tasks using speech inputs in a multi-tasking environment. Further, such techniques alleviate the cumbersomeness or inconvenience associated with performing various tasks in a multi-tasking environment. Furthermore, by allowing the user to perform tasks using speech, they are able to keep both hands on the keyboard or mouse while performing tasking that would require a context switch—effectively, allowing the digital assistant to perform tasks as if a “third-hand” of the user. As will be appreciated, by allowing the user to perform tasks using speech it allows the user to more efficiently complete tasks that may require multiple interactions with multiple applications. For example, searching for images and sending them to an individual in an email may require opening a search interface, entering search terms, selecting one or more results, opening am email for composition, copying or moving the resulting files to the open email, addressing the email and sending it. Such a task can be completed more efficiently by voice with a command such as “find pictures from X date and send them to my wife”. Similar requests for moving files, searching for information on the internet, composing messages can all be made more efficient using voice, while simultaneously allowing the user to perform other tasks using their hands.


Although the following description uses terms “first,” “second,” etc. to describe various elements, these elements should not be limited by the terms. These terms are only used to distinguish one element from another. For example, a first storage could be termed a second storage, and, similarly, a second storage could be termed a first storage, without departing from the scope of the various described examples. The first storage and the second storage can both be storages and, in some cases, can be separate and different storages.


The terminology used in the description of the various described examples herein is for the purpose of describing particular examples only and is not intended to be limiting. As used in the description of the various described examples and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “includes,” “including,” “comprises,” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.


The term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context. Similarly, the phrase “if it is determined” or “if [a stated condition or event] is detected” may be construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event],” depending on the context.


1 System and Environment



FIG. 1 illustrates a block diagram of system 100 according to various examples. In some examples, system 100 can implement a digital assistant. The terms “digital assistant,” “virtual assistant,” “intelligent automated assistant,” or “automatic digital assistant” can refer to any information processing system that interprets natural language input in spoken and/or textual form to infer user intent, and performs actions based on the inferred user intent. For example, to act on an inferred user intent, the system can perform one or more of the following: identifying a task flow with steps and parameters designed to accomplish the inferred user intent, inputting specific requirements from the inferred user intent into the task flow; executing the task flow by invoking programs, methods, services, APIs, or the like; and generating output responses to the user in an audible (e.g., speech) and/or visual form.


Specifically, a digital assistant can be capable of accepting a user request at least partially in the form of a natural language command, request, statement, narrative, and/or inquiry. Typically, the user request can seek either an informational answer or performance of a task by the digital assistant. A satisfactory response to the user request can be a provision of the requested informational answer, a performance of the requested task, or a combination of the two. For example, a user can ask the digital assistant a question, such as “Where am I right now?” Based on the user's current location, the digital assistant can answer, “You are in Central Park near the west gate.” The user can also request the performance of a task, for example, “Please invite my friends to my girlfriend's birthday party next week.” In response, the digital assistant can acknowledge the request by saying “Yes, right away,” and then send a suitable calendar invite on behalf of the user to each of the user's friends listed in the user's electronic address book. During performance of a requested task, the digital assistant can sometimes interact with the user in a continuous dialogue involving multiple exchanges of information over an extended period of time. There are numerous other ways of interacting with a digital assistant to request information or performance of various tasks. In addition to providing verbal responses and taking programmed actions, the digital assistant can also provide responses in other visual or audio forms, e.g., as text, alerts, music, videos, animations, etc.


As shown in FIG. 1, in some examples, a digital assistant can be implemented according to a client-server model. The digital assistant can include client-side portion 102 (hereafter “DA client 102”) executed on user device 104 and server-side portion 106 (hereafter “DA server 106”) executed on server system 108. DA client 102 can communicate with DA server 106 through one or more networks 110. DA client 102 can provide client-side functionalities such as user-facing input and output processing and communication with DA server 106. DA server 106 can provide server-side functionalities for any number of DA clients 102 each residing on a respective user device 104.


In some examples, DA server 106 can include client-facing I/O interface 112, one or more processing modules 114, data and models 116, and I/O interface to external services 118. The client-facing I/O interface 112 can facilitate the client-facing input and output processing for DA server 106. One or more processing modules 114 can utilize data and models 116 to process speech input and determine the user's intent based on natural language input. Further, one or more processing modules 114 perform task execution based on inferred user intent. In some examples, DA server 106 can communicate with external services 120 through network(s) 110 for task completion or information acquisition. I/O interface to external services 118 can facilitate such communications.


User device 104 can be any suitable electronic device. For example, user devices can be a portable multifunctional device (e.g., device 200, described below with reference to FIG. 2A), a multifunctional device (e.g., device 400, described below with reference to FIG. 4), or a personal electronic device (e.g., device 600, described below with reference to FIGS. 6A-6B). A portable multifunctional device can be, for example, a mobile telephone that also contains other functions, such as PDA and/or music player functions. Specific examples of portable multifunction devices can include the iPhone®, iPod Touch®, and iPad® devices from Apple Inc. of Cupertino, California. Other examples of portable multifunction devices can include, without limitation, laptop or tablet computers. Further, in some examples, user device 104 can be a non-portable multifunctional device. In particular, user device 104 can be a desktop computer, a game console, a television, or a television set-top box. In some examples, user device 104 can operate in a multi-tasking environment. A multi-tasking environment allows a user to operate device 104 to perform multiple tasks in parallel. For example, a multi-tasking environment may be a desktop or laptop environment, in which device 104 may perform one task in response to the user input received from a physical user-interface device and, in parallel, perform another task in response to the user's voice input. In some examples, user device 104 can include a touch-sensitive surface (e.g., touch screen displays and/or touchpads). Further, user device 104 can optionally include one or more other physical user-interface devices, such as a physical keyboard, a mouse, and/or a joystick. Various examples of electronic devices, such as multifunctional devices, are described below in greater detail.


Examples of communication network(s) 110 can include local area networks (LAN) and wide area networks (WAN), e.g., the Internet. Communication network(s) 110 can be implemented using any known network protocol, including various wired or wireless protocols, such as, for example, Ethernet, Universal Serial Bus (USB), FIREWIRE, Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Wi-Fi, voice over Internet Protocol (VoIP), Wi-MAX, or any other suitable communication protocol.


Server system 108 can be implemented on one or more standalone data processing apparatus or a distributed network of computers. In some examples, server system 108 can also employ various virtual devices and/or services of third-party service providers (e.g., third-party cloud service providers) to provide the underlying computing resources and/or infrastructure resources of server system 108.


In some examples, user device 104 can communicate with DA server 106 via second user device 122. Second user device 122 can be similar or identical to user device 104. For example, second user device 122 can be similar to devices 200, 400, or 600 described below with reference to FIGS. 2A, 4, and 6A-6B. User device 104 can be configured to communicatively couple to second user device 122 via a direct communication connection, such as Bluetooth, NFC, BTLE, or the like, or via a wired or wireless network, such as a local Wi-Fi network. In some examples, second user device 122 can be configured to act as a proxy between user device 104 and DA server 106. For example, DA client 102 of user device 104 can be configured to transmit information (e.g., a user request received at user device 104) to DA server 106 via second user device 122. DA server 106 can process the information and return relevant data (e.g., data content responsive to the user request) to user device 104 via second user device 122.


In some examples, user device 104 can be configured to communicate abbreviated requests for data to second user device 122 to reduce the amount of information transmitted from user device 104. Second user device 122 can be configured to determine supplemental information to add to the abbreviated request to generate a complete request to transmit to DA server 106. This system architecture can advantageously allow user device 104 having limited communication capabilities and/or limited battery power (e.g., a watch or a similar compact electronic device) to access services provided by DA server 106 by using second user device 122, having greater communication capabilities and/or battery power (e.g., a mobile phone, laptop computer, tablet computer, or the like), as a proxy to DA server 106. While only two user devices 104 and 122 are shown in FIG. 1, it should be appreciated that system 100 can include any number and type of user devices configured in this proxy configuration to communicate with DA server system 106.


Although the digital assistant shown in FIG. 1 can include both a client-side portion (e.g., DA client 102) and a server-side portion (e.g., DA server 106), in some examples, the functions of a digital assistant can be implemented as a standalone application installed on a user device. In addition, the divisions of functionalities between the client and server portions of the digital assistant can vary in different implementations. For instance, in some examples, the DA client can be a thin-client that provides only user-facing input and output processing functions, and delegates all other functionalities of the digital assistant to a backend server.


2. Electronic Devices


Attention is now directed toward embodiments of electronic devices for implementing the client-side portion of a digital assistant. FIG. 2A is a block diagram illustrating portable multifunction device 200 with touch-sensitive display system 212 in accordance with some embodiments. Touch-sensitive display 212 is sometimes called a “touch screen” for convenience and is sometimes known as or called a “touch-sensitive display system.” Device 200 includes memory 202 (which optionally includes one or more computer-readable storage mediums), memory controller 222, one or more processing units (CPUs) 220, peripherals interface 218, RF circuitry 208, audio circuitry 210, speaker 211, microphone 213, input/output (I/O) subsystem 206, other input control devices 216, and external port 224. Device 200 optionally includes one or more optical sensors 264. Device 200 optionally includes one or more contact intensity sensors 265 for detecting intensity of contacts on device 200 (e.g., a touch-sensitive surface such as touch-sensitive display system 212 of device 200). Device 200 optionally includes one or more tactile output generators 267 for generating tactile outputs on device 200 (e.g., generating tactile outputs on a touch-sensitive surface such as touch-sensitive display system 212 of device 200 or touchpad 455 of device 400). These components optionally communicate over one or more communication buses or signal lines 203.


As used in the specification and claims, the term “intensity” of a contact on a touch-sensitive surface refers to the force or pressure (force per unit area) of a contact (e.g., a finger contact) on the touch-sensitive surface or to a substitute (proxy) for the force or pressure of a contact on the touch-sensitive surface. The intensity of a contact has a range of values that includes at least four distinct values and more typically includes hundreds of distinct values (e.g., at least 256). Intensity of a contact is, optionally, determined (or measured) using various approaches and various sensors or combinations of sensors. For example, one or more force sensors underneath or adjacent to the touch-sensitive surface are, optionally, used to measure force at various points on the touch-sensitive surface. In some implementations, force measurements from multiple force sensors are combined (e.g., a weighted average) to determine an estimated force of a contact. Similarly, a pressure-sensitive tip of a stylus is, optionally, used to determine a pressure of the stylus on the touch-sensitive surface. Alternatively, the size of the contact area detected on the touch-sensitive surface and/or changes thereto, the capacitance of the touch-sensitive surface proximate to the contact and/or changes thereto, and/or the resistance of the touch-sensitive surface proximate to the contact and/or changes thereto are, optionally, used as a substitute for the force or pressure of the contact on the touch-sensitive surface. In some implementations, the substitute measurements for contact force or pressure are used directly to determine whether an intensity threshold has been exceeded (e.g., the intensity threshold is described in units corresponding to the substitute measurements). In some implementations, the substitute measurements for contact force or pressure are converted to an estimated force or pressure, and the estimated force or pressure is used to determine whether an intensity threshold has been exceeded (e.g., the intensity threshold is a pressure threshold measured in units of pressure). Using the intensity of a contact as an attribute of a user input allows for user access to additional device functionality that may otherwise not be accessible by the user on a reduced-size device with limited real estate for displaying affordances (e.g., on a touch-sensitive display) and/or receiving user input (e.g., via a touch-sensitive display, a touch-sensitive surface, or a physical/mechanical control such as a knob or a button).


As used in the specification and claims, the term “tactile output” refers to physical displacement of a device relative to a previous position of the device, physical displacement of a component (e.g., a touch-sensitive surface) of a device relative to another component (e.g., housing) of the device, or displacement of the component relative to a center of mass of the device that will be detected by a user with the user's sense of touch. For example, in situations where the device or the component of the device is in contact with a surface of a user that is sensitive to touch (e.g., a finger, palm, or other part of a user's hand), the tactile output generated by the physical displacement will be interpreted by the user as a tactile sensation corresponding to a perceived change in physical characteristics of the device or the component of the device. For example, movement of a touch-sensitive surface (e.g., a touch-sensitive display or trackpad) is, optionally, interpreted by the user as a “down click” or “up click” of a physical actuator button. In some cases, a user will feel a tactile sensation such as an “down click” or “up click” even when there is no movement of a physical actuator button associated with the touch-sensitive surface that is physically pressed (e.g., displaced) by the user's movements. As another example, movement of the touch-sensitive surface is, optionally, interpreted or sensed by the user as “roughness” of the touch-sensitive surface, even when there is no change in smoothness of the touch-sensitive surface. While such interpretations of touch by a user will be subject to the individualized sensory perceptions of the user, there are many sensory perceptions of touch that are common to a large majority of users. Thus, when a tactile output is described as corresponding to a particular sensory perception of a user (e.g., an “up click,” a “down click,” “roughness”), unless otherwise stated, the generated tactile output corresponds to physical displacement of the device or a component thereof that will generate the described sensory perception for a typical (or average) user.


It should be appreciated that device 200 is only one example of a portable multifunction device, and that device 200 optionally has more or fewer components than shown, optionally combines two or more components, or optionally has a different configuration or arrangement of the components. The various components shown in FIG. 2A are implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and/or application-specific integrated circuits.


Memory 202 may include one or more computer-readable storage mediums. The computer-readable storage mediums may be tangible and non-transitory. Memory 202 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices. Memory controller 222 may control access to memory 202 by other components of device 200.


In some examples, a non-transitory computer-readable storage medium of memory 202 can be used to store instructions (e.g., for performing aspects of process 1200, described below) for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. In other examples, the instructions (e.g., for performing aspects of process 1200, described below) can be stored on a non-transitory computer-readable storage medium (not shown) of the server system 108 or can be divided between the non-transitory computer-readable storage medium of memory 202 and the non-transitory computer-readable storage medium of server system 108. In the context of this document, a “non-transitory computer-readable storage medium” can be any medium that can contain or store the program for use by or in connection with the instruction execution system, apparatus, or device.


Peripherals interface 218 can be used to couple input and output peripherals of the device to CPU 220 and memory 202. The one or more processors 220 run or execute various software programs and/or sets of instructions stored in memory 202 to perform various functions for device 200 and to process data. In some embodiments, peripherals interface 218, CPU 220, and memory controller 222 may be implemented on a single chip, such as chip 204. In some other embodiments, they may be implemented on separate chips.


RF (radio frequency) circuitry 208 receives and sends RF signals, also called electromagnetic signals. RF circuitry 208 converts electrical signals to/from electromagnetic signals and communicates with communications networks and other communications devices via the electromagnetic signals. RF circuitry 208 optionally includes well-known circuitry for performing these functions, including but not limited to an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a CODEC chipset, a subscriber identity module (SIM) card, memory, and so forth. RF circuitry 208 optionally communicates with networks, such as the Internet, also referred to as the World Wide Web (WWW), an intranet and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN) and/or a metropolitan area network (MAN), and other devices by wireless communication. The RF circuitry 208 optionally includes well-known circuitry for detecting near field communication (NFC) fields, such as by a short-range communication radio. The wireless communication optionally uses any of a plurality of communications standards, protocols, and technologies, including but not limited to Global System for Mobile Communications (GSM), Enhanced Data GSM Environment (EDGE), high-speed downlink packet access (HSDPA), high-speed uplink packet access (HSUPA), Evolution, Data-Only (EV-DO), HSPA, HSPA+, Dual-Cell HSPA (DC-HSPDA), long term evolution (LTE), near field communication (NFC), wideband code division multiple access (W-CDMA), code division multiple access (CDMA), time division multiple access (TDMA), Bluetooth, Bluetooth Low Energy (BTLE), Wireless Fidelity (Wi-Fi) (e.g., IEEE 802.11a, IEEE 802.11b, IEEE 802.11g, IEEE 802.11n, and/or IEEE 802.11ac), voice over Internet Protocol (VoIP), Wi-MAX, a protocol for e mail (e.g., Internet message access protocol (IMAP) and/or post office protocol (POP)), instant messaging (e.g., extensible messaging and presence protocol (XMPP), Session Initiation Protocol for Instant Messaging and Presence Leveraging Extensions (SIMPLE), Instant Messaging and Presence Service (IMPS)), and/or Short Message Service (SMS), or any other suitable communication protocol, including communication protocols not yet developed as of the filing date of this document.


Audio circuitry 210, speaker 211, and microphone 213 provide an audio interface between a user and device 200. Audio circuitry 210 receives audio data from peripherals interface 218, converts the audio data to an electrical signal, and transmits the electrical signal to speaker 211. Speaker 211 converts the electrical signal to human-audible sound waves. Audio circuitry 210 also receives electrical signals converted by microphone 213 from sound waves. Audio circuitry 210 converts the electrical signal to audio data and transmits the audio data to peripherals interface 218 for processing. Audio data may be retrieved from and/or transmitted to memory 202 and/or RF circuitry 208 by peripherals interface 218. In some embodiments, audio circuitry 210 also includes a headset jack (e.g., 312, FIG. 3). The headset jack provides an interface between audio circuitry 210 and removable audio input/output peripherals, such as output-only headphones or a headset with both output (e.g., a headphone for one or both ears) and input (e.g., a microphone).


I/O subsystem 206 couples input/output peripherals on device 200, such as touch screen 212 and other input control devices 216, to peripherals interface 218. I/O subsystem 206 optionally includes display controller 256, optical sensor controller 258, intensity sensor controller 259, haptic feedback controller 261, and one or more input controllers 260 for other input or control devices. The one or more input controllers 260 receive/send electrical signals from/to other input control devices 216. The other input control devices 216 optionally include physical buttons (e.g., push buttons, rocker buttons, etc.), dials, slider switches, joysticks, click wheels, and so forth. In some alternate embodiments, input controller(s) 260 are, optionally, coupled to any (or none) of the following: a keyboard, an infrared port, a USB port, and a pointer device such as a mouse. The one or more buttons (e.g., 308, FIG. 3) optionally include an up/down button for volume control of speaker 211 and/or microphone 213. The one or more buttons optionally include a push button (e.g., 306, FIG. 3).


A quick press of the push button may disengage a lock of touch screen 212 or begin a process that uses gestures on the touch screen to unlock the device, as described in U.S. patent application Ser. No. 11/322,549, “Unlocking a Device by Performing Gestures on an Unlock Image,” filed Dec. 23, 2005, U.S. Pat. No. 7,657,849, which is hereby incorporated by reference in its entirety. A longer press of the push button (e.g., 306) may turn power to device 200 on or off. The user may be able to customize a functionality of one or more of the buttons. Touch screen 212 is used to implement virtual or soft buttons and one or more soft keyboards.


Touch-sensitive display 212 provides an input interface and an output interface between the device and a user. Display controller 256 receives and/or sends electrical signals from/to touch screen 212. Touch screen 212 displays visual output to the user. The visual output may include graphics, text, icons, video, and any combination thereof (collectively termed “graphics”). In some embodiments, some or all of the visual output may correspond to user interface objects.


Touch screen 212 has a touch-sensitive surface, sensor, or set of sensors that accept input from the user based on haptic and/or tactile contact. Touch screen 212 and display controller 256 (along with any associated modules and/or sets of instructions in memory 202) detect contact (and any movement or breaking of the contact) on touch screen 212 and convert the detected contact into interaction with user interface objects (e.g., one or more soft keys, icons, web pages, or images) that are displayed on touch screen 212. In an exemplary embodiment, a point of contact between touch screen 212 and the user corresponds to a finger of the user.


Touch screen 212 may use LCD (liquid crystal display) technology, LPD (light-emitting polymer display) technology, or LED (light-emitting diode) technology, although other display technologies may be used in other embodiments. Touch screen 212 and display controller 256 may detect contact and any movement or breaking thereof using any of a plurality of touch-sensing technologies now known or later developed, including but not limited to capacitive, resistive, infrared, and surface acoustic wave technologies, as well as other proximity sensor arrays or other elements for determining one or more points of contact with touch screen 212. In an exemplary embodiment, projected mutual capacitance sensing technology is used, such as that found in the iPhone® and iPod Touch® from Apple Inc. of Cupertino, California.


A touch-sensitive display in some embodiments of touch screen 212 may be analogous to the multi-touch sensitive touchpads described in the following U.S. Pat. No. 6,323,846 (Westerman et al.), U.S. Pat. No. 6,570,557 (Westerman et al.), and/or U.S. Pat. No. 6,677,932 (Westerman), and/or U.S. Patent Publication 2002/0015024A1, each of which is hereby incorporated by reference in its entirety. However, touch screen 212 displays visual output from device 200, whereas touch-sensitive touchpads do not provide visual output.


A touch-sensitive display in some embodiments of touch screen 212 may be as described in the following applications: (1) U.S. patent application Ser. No. 11/381,313, “Multipoint Touch Surface Controller,” filed May 2, 2006; (2) U.S. patent application Ser. No. 10/840,862, “Multipoint Touchscreen,” filed May 6, 2004; (3) U.S. patent application Ser. No. 10/903,964, “Gestures For Touch Sensitive Input Devices,” filed Jul. 30, 2004; (4) U.S. patent application Ser. No. 11/048,264, “Gestures For Touch Sensitive Input Devices,” filed Jan. 31, 2005; (5) U.S. patent application Ser. No. 11/038,590, “Mode-Based Graphical User Interfaces For Touch Sensitive Input Devices,” filed Jan. 18, 2005; (6) U.S. patent application Ser. No. 11/228,758, “Virtual Input Device Placement On A Touch Screen User Interface,” filed Sep. 16, 2005; (7) U.S. patent application Ser. No. 11/228,700, “Operation Of A Computer With A Touch Screen Interface,” filed Sep. 16, 2005; (8) U.S. patent application Ser. No. 11/228,737, “Activating Virtual Keys Of A Touch-Screen Virtual Keyboard,” filed Sep. 16, 2005; and (9) U.S. patent application Ser. No. 11/367,749, “Multi-Functional Hand-Held Device,” filed Mar. 3, 2006. All of these applications are incorporated by reference herein in their entirety.


Touch screen 212 may have a video resolution in excess of 100 dpi. In some embodiments, the touch screen has a video resolution of approximately 160 dpi. The user may make contact with touch screen 212 using any suitable object or appendage, such as a stylus, a finger, and so forth. In some embodiments, the user interface is designed to work primarily with finger-based contacts and gestures, which can be less precise than stylus-based input due to the larger area of contact of a finger on the touch screen. In some embodiments, the device translates the rough finger-based input into a precise pointer/cursor position or command for performing the actions desired by the user.


In some embodiments, in addition to the touch screen, device 200 may include a touchpad (not shown) for activating or deactivating particular functions. In some embodiments, the touchpad is a touch-sensitive area of the device that, unlike the touch screen, does not display visual output. The touchpad may be a touch-sensitive surface that is separate from touch screen 212 or an extension of the touch-sensitive surface formed by the touch screen.


Device 200 also includes power system 262 for powering the various components. Power system 262 may include a power management system, one or more power sources (e.g., battery or alternating current (AC)), a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator (e.g., a light-emitting diode) and any other components associated with the generation, management, and distribution of power in portable devices.


Device 200 may also include one or more optical sensors 264. FIG. 2A shows an optical sensor coupled to optical sensor controller 258 in I/O subsystem 206. Optical sensor 264 may include charge-coupled device (CCD) or complementary metal-oxide semiconductor (CMOS) phototransistors. Optical sensor 264 receives light from the environment, projected through one or more lenses, and converts the light to data representing an image. In conjunction with imaging module 243 (also called a camera module), optical sensor 264 may capture still images or video. In some embodiments, an optical sensor is located on the back of device 200, opposite touch screen display 212 on the front of the device so that the touch screen display may be used as a viewfinder for still and/or video image acquisition. In some embodiments, an optical sensor is located on the front of the device, so that the user's image may be obtained for video conferencing while the user views the other video conference participants on the touch screen display. In some embodiments, the position of optical sensor 264 can be changed by the user (e.g., by rotating the lens and the sensor in the device housing) so that a single optical sensor 264 may be used along with the touch screen display for both video conferencing and still and/or video image acquisition.


Device 200 optionally also includes one or more contact intensity sensors 265. FIG. 2A shows a contact intensity sensor coupled to intensity sensor controller 259 in I/O subsystem 206. Contact intensity sensor 265 optionally includes one or more piezoresistive strain gauges, capacitive force sensors, electric force sensors, piezoelectric force sensors, optical force sensors, capacitive touch-sensitive surfaces, or other intensity sensors (e.g., sensors used to measure the force (or pressure) of a contact on a touch-sensitive surface). Contact intensity sensor 265 receives contact intensity information (e.g., pressure information or a proxy for pressure information) from the environment. In some embodiments, at least one contact intensity sensor is collocated with, or proximate to, a touch-sensitive surface (e.g., touch-sensitive display system 212). In some embodiments, at least one contact intensity sensor is located on the back of device 200, opposite touch screen display 212, which is located on the front of device 200.


Device 200 may also include one or more proximity sensors 266. FIG. 2A shows proximity sensor 266 coupled to peripherals interface 218. Alternately, proximity sensor 266 may be coupled to input controller 260 in I/O subsystem 206. Proximity sensor 266 may perform as described in U.S. patent application Ser. No. 11/241,839, “Proximity Detector In Handheld Device”; Ser. No. 11/240,788, “Proximity Detector In Handheld Device”; Ser. No. 11/620,702, “Using Ambient Light Sensor To Augment Proximity Sensor Output”; Ser. No. 11/586,862, “Automated Response To And Sensing Of User Activity In Portable Devices”; and Ser. No. 11/638,251, “Methods And Systems For Automatic Configuration Of Peripherals,” which are hereby incorporated by reference in their entirety. In some embodiments, the proximity sensor turns off and disables touch screen 212 when the multifunction device is placed near the user's ear (e.g., when the user is making a phone call).


Device 200 optionally also includes one or more tactile output generators 267. FIG. 2A shows a tactile output generator coupled to haptic feedback controller 261 in I/O subsystem 206. Tactile output generator 267 optionally includes one or more electroacoustic devices such as speakers or other audio components and/or electromechanical devices that convert energy into linear motion such as a motor, solenoid, electroactive polymer, piezoelectric actuator, electrostatic actuator, or other tactile output generating component (e.g., a component that converts electrical signals into tactile outputs on the device). Contact intensity sensor 265 receives tactile feedback generation instructions from haptic feedback module 233 and generates tactile outputs on device 200 that are capable of being sensed by a user of device 200. In some embodiments, at least one tactile output generator is collocated with, or proximate to, a touch-sensitive surface (e.g., touch-sensitive display system 212) and, optionally, generates a tactile output by moving the touch-sensitive surface vertically (e.g., in/out of a surface of device 200) or laterally (e.g., back and forth in the same plane as a surface of device 200). In some embodiments, at least one tactile output generator sensor is located on the back of device 200, opposite touch screen display 212, which is located on the front of device 200.


Device 200 may also include one or more accelerometers 268. FIG. 2A shows accelerometer 268 coupled to peripherals interface 218. Alternately, accelerometer 268 may be coupled to an input controller 260 in I/O subsystem 206. Accelerometer 268 may perform as described in U.S. Patent Publication No. 20050190059, “Acceleration-based Theft Detection System for Portable Electronic Devices,” and U.S. Patent Publication No. 20060017692, “Methods And Apparatuses For Operating A Portable Device Based On An Accelerometer,” both of which are incorporated by reference herein in their entirety. In some embodiments, information is displayed on the touch screen display in a portrait view or a landscape view based on an analysis of data received from the one or more accelerometers. Device 200 optionally includes, in addition to accelerometer(s) 268, a magnetometer (not shown) and a GPS (or GLONASS or other global navigation system) receiver (not shown) for obtaining information concerning the location and orientation (e.g., portrait or landscape) of device 200.


In some embodiments, the software components stored in memory 202 include operating system 226, communication module (or set of instructions) 228, contact/motion module (or set of instructions) 230, graphics module (or set of instructions) 232, text input module (or set of instructions) 234, Global Positioning System (GPS) module (or set of instructions) 235, Digital Assistant Client Module 229, and applications (or sets of instructions) 236. Further, memory 202 can store data and models, such as user data and models 231. Furthermore, in some embodiments, memory 202 (FIG. 2A) or 470 (FIG. 4) stores device/global internal state 257, as shown in FIGS. 2A and 4. Device/global internal state 257 includes one or more of: active application state, indicating which applications, if any, are currently active; display state, indicating what applications, views, or other information occupy various regions of touch screen display 212; sensor state, including information obtained from the device's various sensors and input control devices 216; and location information concerning the device's location and/or attitude.


Operating system 226 (e.g., Darwin, RTXC, LINUX, UNIX, OS X, iOS, WINDOWS, or an embedded operating system such as VxWorks) includes various software components and/or drivers for controlling and managing general system tasks (e.g., memory management, storage device control, power management, etc.) and facilitates communication between various hardware and software components.


Communication module 228 facilitates communication with other devices over one or more external ports 224 and also includes various software components for handling data received by RF circuitry 208 and/or external port 224. External port 224 (e.g., Universal Serial Bus (USB), FIREWIRE, etc.) is adapted for coupling directly to other devices or indirectly over a network (e.g., the Internet, wireless LAN, etc.). In some embodiments, the external port is a multi-pin (e.g., 30-pin) connector that is the same as, or similar to and/or compatible with, the 30-pin connector used on iPod® (trademark of Apple Inc.) devices.


Contact/motion module 230 optionally detects contact with touch screen 212 (in conjunction with display controller 256) and other touch-sensitive devices (e.g., a touchpad or physical click wheel). Contact/motion module 230 includes various software components for performing various operations related to detection of contact, such as determining if contact has occurred (e.g., detecting a finger-down event), determining an intensity of the contact (e.g., the force or pressure of the contact or a substitute for the force or pressure of the contact), determining if there is movement of the contact and tracking the movement across the touch-sensitive surface (e.g., detecting one or more finger-dragging events), and determining if the contact has ceased (e.g., detecting a finger-up event or a break in contact). Contact/motion module 230 receives contact data from the touch-sensitive surface. Determining movement of the point of contact, which is represented by a series of contact data, optionally includes determining speed (magnitude), velocity (magnitude and direction), and/or an acceleration (a change in magnitude and/or direction) of the point of contact. These operations are, optionally, applied to single contacts (e.g., one finger contacts) or to multiple simultaneous contacts (e.g., “multitouch”/multiple finger contacts). In some embodiments, contact/motion module 230 and display controller 256 detect contact on a touchpad.


In some embodiments, contact/motion module 230 uses a set of one or more intensity thresholds to determine whether an operation has been performed by a user (e.g., to determine whether a user has “clicked” on an icon). In some embodiments, at least a subset of the intensity thresholds are determined in accordance with software parameters (e.g., the intensity thresholds are not determined by the activation thresholds of particular physical actuators and can be adjusted without changing the physical hardware of device 200). For example, a mouse “click” threshold of a trackpad or touch screen display can be set to any of a large range of predefined threshold values without changing the trackpad or touch screen display hardware. Additionally, in some implementations, a user of the device is provided with software settings for adjusting one or more of the set of intensity thresholds (e.g., by adjusting individual intensity thresholds and/or by adjusting a plurality of intensity thresholds at once with a system-level click “intensity” parameter).


Contact/motion module 230 optionally detects a gesture input by a user. Different gestures on the touch-sensitive surface have different contact patterns (e.g., different motions, timings, and/or intensities of detected contacts). Thus, a gesture is, optionally, detected by detecting a particular contact pattern. For example, detecting a finger tap gesture includes detecting a finger-down event followed by detecting a finger-up (liftoff) event at the same position (or substantially the same position) as the finger-down event (e.g., at the position of an icon). As another example, detecting a finger swipe gesture on the touch-sensitive surface includes detecting a finger-down event followed by detecting one or more finger-dragging events, and subsequently followed by detecting a finger-up (liftoff) event.


Graphics module 232 includes various known software components for rendering and displaying graphics on touch screen 212 or other display, including components for changing the visual impact (e.g., brightness, transparency, saturation, contrast, or other visual property) of graphics that are displayed. As used herein, the term “graphics” includes any object that can be displayed to a user, including, without limitation, text, web pages, icons (such as user-interface objects including soft keys), digital images, videos, animations, and the like.


In some embodiments, graphics module 232 stores data representing graphics to be used. Each graphic is, optionally, assigned a corresponding code. Graphics module 232 receives, from applications etc., one or more codes specifying graphics to be displayed along with, if necessary, coordinate data and other graphic property data and then generates screen image data to output to display controller 256.


Haptic feedback module 233 includes various software components for generating instructions used by tactile output generator(s) 267 to produce tactile outputs at one or more locations on device 200 in response to user interactions with device 200.


Text input module 234, which may be a component of graphics module 232, provides soft keyboards for entering text in various applications (e.g., contacts module 237, e-mail client module 240, IM module 241, browser module 247, and any other application that needs text input).


GPS module 235 determines the location of the device and provides this information for use in various applications (e.g., to telephone module 238 for use in location-based dialing; to camera module 243 as picture/video metadata; and to applications that provide location-based services such as weather widgets, local yellow page widgets, and map/navigation widgets).


Digital assistant client module 229 can include various client-side digital assistant instructions to provide the client-side functionalities of the digital assistant. For example, digital assistant client module 229 can be capable of accepting voice input (e.g., speech input), text input, touch input, and/or gestural input through various user interfaces (e.g., microphone 213, accelerometer(s) 268, touch-sensitive display system 212, optical sensor(s) 264, other input control devices 216, etc.) of portable multifunction device 200. Digital assistant client module 229 can also be capable of providing output in audio (e.g., speech output), visual, and/or tactile forms through various output interfaces (e.g., speaker 211, touch-sensitive display system 212, tactile output generator(s) 267, etc.) of portable multifunction device 200. For example, output can be provided as voice, sound, alerts, text messages, menus, graphics, videos, animations, vibrations, and/or combinations of two or more of the above. During operation, digital assistant client module 229 can communicate with DA server 106 using RF circuitry 208.


User data and models 231 can include various data associated with the user (e.g., user-specific vocabulary data, user preference data, user-specified name pronunciations, data from the user's electronic address book, to-do lists, shopping lists, etc.) to provide the client-side functionalities of the digital assistant. Further, user data and models 231 can includes various models (e.g., speech recognition models, statistical language models, natural language processing models, ontology, task flow models, service models, etc.) for processing user input and determining user intent.


In some examples, digital assistant client module 229 can utilize the various sensors, subsystems, and peripheral devices of portable multifunction device 200 to gather additional information from the surrounding environment of the portable multifunction device 200 to establish a context associated with a user, the current user interaction, and/or the current user input. In some examples, digital assistant client module 229 can provide the contextual information or a subset thereof with the user input to DA server 106 to help infer the user's intent. In some examples, the digital assistant can also use the contextual information to determine how to prepare and deliver outputs to the user. Contextual information can be referred to as context data.


In some examples, the contextual information that accompanies the user input can include sensor information, e.g., lighting, ambient noise, ambient temperature, images or videos of the surrounding environment, etc. In some examples, the contextual information can also include the physical state of the device, e.g., device orientation, device location, device temperature, power level, speed, acceleration, motion patterns, cellular signals strength, etc. In some examples, information related to the software state of DA server 106, e.g., running processes, installed programs, past and present network activities, background services, error logs, resources usage, etc., and of portable multifunction device 200 can be provided to DA server 106 as contextual information associated with a user input.


In some examples, the digital assistant client module 229 can selectively provide information (e.g., user data 231) stored on the portable multifunction device 200 in response to requests from DA server 106. In some examples, digital assistant client module 229 can also elicit additional input from the user via a natural language dialogue or other user interfaces upon request by DA server 106. Digital assistant client module 229 can pass the additional input to DA server 106 to help DA server 106 in intent deduction and/or fulfillment of the user's intent expressed in the user request.


A more detailed description of a digital assistant is described below with reference to FIGS. 7A-7C. It should be recognized that digital assistant client module 229 can include any number of the sub-modules of digital assistant module 726 described below.


Applications 236 may include the following modules (or sets of instructions), or a subset or superset thereof:

    • Contacts module 237 (sometimes called an address book or contact list);
    • Telephone module 238;
    • Video conference module 239;
    • Email client module 240;
    • Instant messaging (IM) module 241;
    • Workout support module 242;
    • Camera module 243 for still and/or video images;
    • Image management module 244;
    • Video player module;
    • Music player module;
    • Browser module 247;
    • Calendar module 248;
    • Widget modules 249, which may include one or more of: weather widget 249-1, stocks widget 249-2, calculator widget 249-3, alarm clock widget 249-4, dictionary widget 249-5, and other widgets obtained by the user, as well as user-created widgets 249-6;
    • Widget creator module 250 for making user-created widgets 249-6;
    • Search module 251;
    • Video and music player module 252, which merges video player module and music player module;
    • Notes module 253;
    • Map module 254; and/or
    • Online video module 255.


Examples of other applications 236 that may be stored in memory 202 include other word processing applications, other image editing applications, drawing applications, presentation applications, JAVA-enabled applications, encryption, digital rights management, voice recognition, and voice replication.


In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, contacts module 237 may be used to manage an address book or contact list (e.g., stored in application internal state 292 of contacts module 237 in memory 202 or memory 470), including: adding name(s) to the address book; deleting name(s) from the address book; associating telephone number(s), email address(es), physical address(es) or other information with a name; associating an image with a name; categorizing and sorting names; providing telephone numbers or email addresses to initiate and/or facilitate communications by telephone module 238, video conference module 239, e-mail client module 240, or IM module 241; and so forth.


In conjunction with RF circuitry 208, audio circuitry 210, speaker 211, microphone 213, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, telephone module 238 may be used to enter a sequence of characters corresponding to a telephone number, access one or more telephone numbers in contacts module 237, modify a telephone number that has been entered, dial a respective telephone number, conduct a conversation, and disconnect or hang up when the conversation is completed. As noted above, the wireless communication may use any of a plurality of communications standards, protocols, and technologies.


In conjunction with RF circuitry 208, audio circuitry 210, speaker 211, microphone 213, touch screen 212, display controller 256, optical sensor 264, optical sensor controller 258, contact/motion module 230, graphics module 232, text input module 234, contacts module 237, and telephone module 238, video conference module 239 includes executable instructions to initiate, conduct, and terminate a video conference between a user and one or more other participants in accordance with user instructions.


In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, email client module 240 includes executable instructions to create, send, receive, and manage email in response to user instructions. In conjunction with image management module 244, email client module 240 makes it very easy to create and send emails with still or video images taken with camera module 243.


In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, instant messaging module 241 includes executable instructions to enter a sequence of characters corresponding to an instant message, to modify previously entered characters, to transmit a respective instant message (for example, using a Short Message Service (SMS) or Multimedia Message Service (MMS) protocol for telephony-based instant messages or using XMPP, SIMPLE, or IMPS for Internet-based instant messages), to receive instant messages, and to view received instant messages. In some embodiments, transmitted and/or received instant messages may include graphics, photos, audio files, video files, and/or other attachments as are supported in an MMS and/or an Enhanced Messaging Service (EMS). As used herein, “instant messaging” refers to both telephony-based messages (e.g., messages sent using SMS or MMS) and Internet-based messages (e.g., messages sent using XMPP, SIMPLE, or IMPS).


In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, GPS module 235, map module 254, and music player module, workout support module 242 includes executable instructions to create workouts (e.g., with time, distance, and/or calorie burning goals); communicate with workout sensors (sports devices); receive workout sensor data; calibrate sensors used to monitor a workout; select and play music for a workout; and display, store, and transmit workout data.


In conjunction with touch screen 212, display controller 256, optical sensor(s) 264, optical sensor controller 258, contact/motion module 230, graphics module 232, and image management module 244, camera module 243 includes executable instructions to capture still images or video (including a video stream) and store them into memory 202, modify characteristics of a still image or video, or delete a still image or video from memory 202.


In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, and camera module 243, image management module 244 includes executable instructions to arrange, modify (e.g., edit), or otherwise manipulate, label, delete, present (e.g., in a digital slide show or album), and store still and/or video images.


In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, browser module 247 includes executable instructions to browse the Internet in accordance with user instructions, including searching, linking to, receiving, and displaying web pages or portions thereof, as well as attachments and other files linked to web pages.


In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, email client module 240, and browser module 247, calendar module 248 includes executable instructions to create, display, modify, and store calendars and data associated with calendars (e.g., calendar entries, to-do lists, etc.) in accordance with user instructions.


In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, and browser module 247, widget modules 249 are mini-applications that may be downloaded and used by a user (e.g., weather widget 249-1, stocks widget 249-2, calculator widget 249-3, alarm clock widget 249-4, and dictionary widget 249-5) or created by the user (e.g., user-created widget 249-6). In some embodiments, a widget includes an HTML (Hypertext Markup Language) file, a CSS (Cascading Style Sheets) file, and a JavaScript file. In some embodiments, a widget includes an XML (Extensible Markup Language) file and a JavaScript file (e.g., Yahoo! Widgets).


In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, and browser module 247, the widget creator module 250 may be used by a user to create widgets (e.g., turning a user-specified portion of a web page into a widget).


In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, search module 251 includes executable instructions to search for text, music, sound, image, video, and/or other files in memory 202 that match one or more search criteria (e.g., one or more user-specified search terms) in accordance with user instructions.


In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, audio circuitry 210, speaker 211, RF circuitry 208, and browser module 247, video and music player module 252 includes executable instructions that allow the user to download and play back recorded music and other sound files stored in one or more file formats, such as MP3 or AAC files, and executable instructions to display, present, or otherwise play back videos (e.g., on touch screen 212 or on an external, connected display via external port 224). In some embodiments, device 200 optionally includes the functionality of an MP3 player, such as an iPod (trademark of Apple Inc.).


In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, notes module 253 includes executable instructions to create and manage notes, to-do lists, and the like in accordance with user instructions.


In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, GPS module 235, and browser module 247, map module 254 may be used to receive, display, modify, and store maps and data associated with maps (e.g., driving directions, data on stores and other points of interest at or near a particular location, and other location-based data) in accordance with user instructions.


In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, audio circuitry 210, speaker 211, RF circuitry 208, text input module 234, email client module 240, and browser module 247, online video module 255 includes instructions that allow the user to access, browse, receive (e.g., by streaming and/or download), play back (e.g., on the touch screen or on an external, connected display via external port 224), send an email with a link to a particular online video, and otherwise manage online videos in one or more file formats, such as H.264. In some embodiments, instant messaging module 241, rather than email client module 240, is used to send a link to a particular online video. Additional description of the online video application can be found in U.S. Provisional Patent Application No. 60/936,562, “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” filed Jun. 20, 2007, and U.S. patent application Ser. No. 11/968,067, “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” filed Dec. 31, 2007, the contents of which are hereby incorporated by reference in their entirety.


Each of the above-identified modules and applications corresponds to a set of executable instructions for performing one or more functions described above and the methods described in this application (e.g., the computer-implemented methods and other information processing methods described herein). These modules (e.g., sets of instructions) need not be implemented as separate software programs, procedures, or modules, and thus various subsets of these modules may be combined or otherwise rearranged in various embodiments. For example, video player module may be combined with music player module into a single module (e.g., video and music player module 252, FIG. 2A). In some embodiments, memory 202 may store a subset of the modules and data structures identified above. Furthermore, memory 202 may store additional modules and data structures not described above.


In some embodiments, device 200 is a device where operation of a predefined set of functions on the device is performed exclusively through a touch screen and/or a touchpad. By using a touch screen and/or a touchpad as the primary input control device for operation of device 200, the number of physical input control devices (such as push buttons, dials, and the like) on device 200 may be reduced.


The predefined set of functions that are performed exclusively through a touch screen and/or a touchpad optionally include navigation between user interfaces. In some embodiments, the touchpad, when touched by the user, navigates device 200 to a main, home, or root menu from any user interface that is displayed on device 200. In such embodiments, a “menu button” is implemented using a touchpad. In some other embodiments, the menu button is a physical push button or other physical input control device instead of a touchpad.



FIG. 2B is a block diagram illustrating exemplary components for event handling in accordance with some embodiments. In some embodiments, memory 202 (FIG. 2A) or 470 (FIG. 4) includes event sorter 270 (e.g., in operating system 226) and a respective application 236-1 (e.g., any of the aforementioned applications 237-251, 255, 480-490).


Event sorter 270 receives event information and determines the application 236-1 and application view 291 of application 236-1 to which to deliver the event information. Event sorter 270 includes event monitor 271 and event dispatcher module 274. In some embodiments, application 236-1 includes application internal state 292, which indicates the current application view(s) displayed on touch-sensitive display 212 when the application is active or executing. In some embodiments, device/global internal state 257 is used by event sorter 270 to determine which application(s) is (are) currently active, and application internal state 292 is used by event sorter 270 to determine application views 291 to which to deliver event information.


In some embodiments, application internal state 292 includes additional information, such as one or more of: resume information to be used when application 236-1 resumes execution, user interface state information that indicates information being displayed or that is ready for display by application 236-1, a state queue for enabling the user to go back to a prior state or view of application 236-1, and a redo/undo queue of previous actions taken by the user.


Event monitor 271 receives event information from peripherals interface 218. Event information includes information about a sub-event (e.g., a user touch on touch-sensitive display 212, as part of a multi-touch gesture). Peripherals interface 218 transmits information it receives from I/O subsystem 206 or a sensor, such as proximity sensor 266, accelerometer(s) 268, and/or microphone 213 (through audio circuitry 210). Information that peripherals interface 218 receives from I/O subsystem 206 includes information from touch-sensitive display 212 or a touch-sensitive surface.


In some embodiments, event monitor 271 sends requests to the peripherals interface 218 at predetermined intervals. In response, peripherals interface 218 transmits event information. In other embodiments, peripherals interface 218 transmits event information only when there is a significant event (e.g., receiving an input above a predetermined noise threshold and/or for more than a predetermined duration).


In some embodiments, event sorter 270 also includes a hit view determination module 272 and/or an active event recognizer determination module 273.


Hit view determination module 272 provides software procedures for determining where a sub-event has taken place within one or more views when touch-sensitive display 212 displays more than one view. Views are made up of controls and other elements that a user can see on the display.


Another aspect of the user interface associated with an application is a set of views, sometimes herein called application views or user interface windows, in which information is displayed and touch-based gestures occur. The application views (of a respective application) in which a touch is detected may correspond to programmatic levels within a programmatic or view hierarchy of the application. For example, the lowest level view in which a touch is detected may be called the hit view, and the set of events that are recognized as proper inputs may be determined based, at least in part, on the hit view of the initial touch that begins a touch-based gesture.


Hit view determination module 272 receives information related to sub events of a touch-based gesture. When an application has multiple views organized in a hierarchy, hit view determination module 272 identifies a hit view as the lowest view in the hierarchy which should handle the sub-event. In most circumstances, the hit view is the lowest level view in which an initiating sub-event occurs (e.g., the first sub-event in the sequence of sub-events that form an event or potential event). Once the hit view is identified by the hit view determination module 272, the hit view typically receives all sub-events related to the same touch or input source for which it was identified as the hit view.


Active event recognizer determination module 273 determines which view or views within a view hierarchy should receive a particular sequence of sub-events. In some embodiments, active event recognizer determination module 273 determines that only the hit view should receive a particular sequence of sub-events. In other embodiments, active event recognizer determination module 273 determines that all views that include the physical location of a sub-event are actively involved views and therefore determines that all actively involved views should receive a particular sequence of sub-events. In other embodiments, even if touch sub-events were entirely confined to the area associated with one particular view, views higher in the hierarchy would still remain as actively involved views.


Event dispatcher module 274 dispatches the event information to an event recognizer (e.g., event recognizer 280). In embodiments including active event recognizer determination module 273, event dispatcher module 274 delivers the event information to an event recognizer determined by active event recognizer determination module 273. In some embodiments, event dispatcher module 274 stores in an event queue the event information, which is retrieved by a respective event receiver 282.


In some embodiments, operating system 226 includes event sorter 270. Alternatively, application 236-1 includes event sorter 270. In yet other embodiments, event sorter 270 is a stand-alone module or a part of another module stored in memory 202, such as contact/motion module 230.


In some embodiments, application 236-1 includes a plurality of event handlers 290 and one or more application views 291, each of which includes instructions for handling touch events that occur within a respective view of the application's user interface. Each application view 291 of the application 236-1 includes one or more event recognizers 280. Typically, a respective application view 291 includes a plurality of event recognizers 280. In other embodiments, one or more of event recognizers 280 are part of a separate module, such as a user interface kit (not shown) or a higher level object from which application 236-1 inherits methods and other properties. In some embodiments, a respective event handler 290 includes one or more of: data updater 276, object updater 277, GUI updater 278, and/or event data 279 received from event sorter 270. Event handler 290 may utilize or call data updater 276, object updater 277, or GUI updater 278 to update the application internal state 292. Alternatively, one or more of the application views 291 include one or more respective event handlers 290. Also, in some embodiments, one or more of data updater 276, object updater 277, and GUI updater 278 are included in a respective application view 291.


A respective event recognizer 280 receives event information (e.g., event data 279) from event sorter 270 and identifies an event from the event information. Event recognizer 280 includes event receiver 282 and event comparator 284. In some embodiments, event recognizer 280 also includes at least a subset of: metadata 283 and event delivery instructions 288 (which may include sub-event delivery instructions).


Event receiver 282 receives event information from event sorter 270. The event information includes information about a sub-event, for example, a touch or a touch movement. Depending on the sub-event, the event information also includes additional information, such as location of the sub-event. When the sub-event concerns motion of a touch, the event information may also include speed and direction of the sub-event. In some embodiments, events include rotation of the device from one orientation to another (e.g., from a portrait orientation to a landscape orientation, or vice versa), and the event information includes corresponding information about the current orientation (also called device attitude) of the device.


Event comparator 284 compares the event information to predefined event or sub-event definitions and, based on the comparison, determines an event or sub event, or determines or updates the state of an event or sub-event. In some embodiments, event comparator 284 includes event definitions 286. Event definitions 286 contain definitions of events (e.g., predefined sequences of sub-events), for example, event 1 (287-1), event 2 (287-2), and others. In some embodiments, sub-events in an event (287) include, for example, touch begin, touch end, touch movement, touch cancellation, and multiple touching. In one example, the definition for event 1 (287-1) is a double tap on a displayed object. The double tap, for example, comprises a first touch (touch begin) on the displayed object for a predetermined phase, a first liftoff (touch end) for a predetermined phase, a second touch (touch begin) on the displayed object for a predetermined phase, and a second liftoff (touch end) for a predetermined phase. In another example, the definition for event 2 (287-2) is a dragging on a displayed object. The dragging, for example, comprises a touch (or contact) on the displayed object for a predetermined phase, a movement of the touch across touch-sensitive display 212, and liftoff of the touch (touch end). In some embodiments, the event also includes information for one or more associated event handlers 290.


In some embodiments, event definition 287 includes a definition of an event for a respective user-interface object. In some embodiments, event comparator 284 performs a hit test to determine which user-interface object is associated with a sub-event. For example, in an application view in which three user-interface objects are displayed on touch-sensitive display 212, when a touch is detected on touch-sensitive display 212, event comparator 284 performs a hit test to determine which of the three user-interface objects is associated with the touch (sub-event). If each displayed object is associated with a respective event handler 290, the event comparator uses the result of the hit test to determine which event handler 290 should be activated. For example, event comparator 284 selects an event handler associated with the sub-event and the object triggering the hit test.


In some embodiments, the definition for a respective event (287) also includes delayed actions that delay delivery of the event information until after it has been determined whether the sequence of sub-events does or does not correspond to the event recognizer's event type.


When a respective event recognizer 280 determines that the series of sub-events do not match any of the events in event definitions 286, the respective event recognizer 280 enters an event impossible, event failed, or event ended state, after which it disregards subsequent sub-events of the touch-based gesture. In this situation, other event recognizers, if any, that remain active for the hit view continue to track and process sub-events of an ongoing touch-based gesture.


In some embodiments, a respective event recognizer 280 includes metadata 283 with configurable properties, flags, and/or lists that indicate how the event delivery system should perform sub-event delivery to actively involved event recognizers. In some embodiments, metadata 283 includes configurable properties, flags, and/or lists that indicate how event recognizers may interact, or are enabled to interact, with one another. In some embodiments, metadata 283 includes configurable properties, flags, and/or lists that indicate whether sub-events are delivered to varying levels in the view or programmatic hierarchy.


In some embodiments, a respective event recognizer 280 activates event handler 290 associated with an event when one or more particular sub-events of an event are recognized. In some embodiments, a respective event recognizer 280 delivers event information associated with the event to event handler 290. Activating an event handler 290 is distinct from sending (and deferred sending) sub-events to a respective hit view. In some embodiments, event recognizer 280 throws a flag associated with the recognized event, and event handler 290 associated with the flag catches the flag and performs a predefined process.


In some embodiments, event delivery instructions 288 include sub-event delivery instructions that deliver event information about a sub-event without activating an event handler. Instead, the sub-event delivery instructions deliver event information to event handlers associated with the series of sub-events or to actively involved views. Event handlers associated with the series of sub-events or with actively involved views receive the event information and perform a predetermined process.


In some embodiments, data updater 276 creates and updates data used in application 236-1. For example, data updater 276 updates the telephone number used in contacts module 237, or stores a video file used in video player module. In some embodiments, object updater 277 creates and updates objects used in application 236-1. For example, object updater 277 creates a new user-interface object or updates the position of a user-interface object. GUI updater 278 updates the GUI. For example, GUI updater 278 prepares display information and sends it to graphics module 232 for display on a touch-sensitive display.


In some embodiments, event handler(s) 290 includes or has access to data updater 276, object updater 277, and GUI updater 278. In some embodiments, data updater 276, object updater 277, and GUI updater 278 are included in a single module of a respective application 236-1 or application view 291. In other embodiments, they are included in two or more software modules.


It shall be understood that the foregoing discussion regarding event handling of user touches on touch-sensitive displays also applies to other forms of user inputs to operate multifunction devices 200 with input devices, not all of which are initiated on touch screens. For example, mouse movement and mouse button presses, optionally coordinated with single or multiple keyboard presses or holds; contact movements such as taps, drags, scrolls, etc. on touchpads; pen stylus inputs; movement of the device; oral instructions; detected eye movements; biometric inputs; and/or any combination thereof are optionally utilized as inputs corresponding to sub-events which define an event to be recognized.



FIG. 3 illustrates a portable multifunction device 200 having a touch screen 212 in accordance with some embodiments. The touch screen optionally displays one or more graphics within user interface (UI) 300. In this embodiment, as well as others described below, a user is enabled to select one or more of the graphics by making a gesture on the graphics, for example, with one or more fingers 302 (not drawn to scale in the figure) or one or more styluses 303 (not drawn to scale in the figure). In some embodiments, selection of one or more graphics occurs when the user breaks contact with the one or more graphics. In some embodiments, the gesture optionally includes one or more taps, one or more swipes (from left to right, right to left, upward, and/or downward), and/or a rolling of a finger (from right to left, left to right, upward, and/or downward) that has made contact with device 200. In some implementations or circumstances, inadvertent contact with a graphic does not select the graphic. For example, a swipe gesture that sweeps over an application icon optionally does not select the corresponding application when the gesture corresponding to selection is a tap.


Device 200 may also include one or more physical buttons, such as “home” or menu button 304. As described previously, menu button 304 may be used to navigate to any application 236 in a set of applications that may be executed on device 200. Alternatively, in some embodiments, the menu button is implemented as a soft key in a GUI displayed on touch screen 212.


In one embodiment, device 200 includes touch screen 212, menu button 304, push button 306 for powering the device on/off and locking the device, volume adjustment button(s) 308, subscriber identity module (SIM) card slot 310, headset jack 312, and docking/charging external port 224. Push button 306 is, optionally, used to turn the power on/off on the device by depressing the button and holding the button in the depressed state for a predefined time interval; to lock the device by depressing the button and releasing the button before the predefined time interval has elapsed; and/or to unlock the device or initiate an unlock process. In an alternative embodiment, device 200 also accepts verbal input for activation or deactivation of some functions through microphone 213. Device 200 also, optionally, includes one or more contact intensity sensors 265 for detecting intensity of contacts on touch screen 212 and/or one or more tactile output generators 267 for generating tactile outputs for a user of device 200.



FIG. 4 is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface in accordance with some embodiments. Device 400 need not be portable. In some embodiments, device 400 is a laptop computer, a desktop computer, a tablet computer, a multimedia player device, a navigation device, an educational device (such as a child's learning toy), a gaming system, or a control device (e.g., a home or industrial controller). Device 400 typically includes one or more processing units (CPUs) 410, one or more network or other communications interfaces 460, memory 470, and one or more communication buses 420 for interconnecting these components. Communication buses 420 optionally include circuitry (sometimes called a chipset) that interconnects and controls communications between system components. Device 400 includes input/output (I/O) interface 430 comprising display 440, which is typically a touch screen display. I/O interface 430 also optionally includes a keyboard and/or mouse (or other pointing device) 450 and touchpad 455, tactile output generator 457 for generating tactile outputs on device 400 (e.g., similar to tactile output generator(s) 267 described above with reference to FIG. 2A), sensors 459 (e.g., optical, acceleration, proximity, touch-sensitive, and/or contact intensity sensors similar to contact intensity sensor(s) 265 described above with reference to FIG. 2A). Memory 470 includes high-speed random access memory, such as DRAM, SRAM, DDR RAM, or other random access solid state memory devices; and optionally includes non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices. Memory 470 optionally includes one or more storage devices remotely located from CPU(s) 410. In some embodiments, memory 470 stores programs, modules, and data structures analogous to the programs, modules, and data structures stored in memory 202 of portable multifunction device 200 (FIG. 2A), or a subset thereof. Furthermore, memory 470 optionally stores additional programs, modules, and data structures not present in memory 202 of portable multifunction device 200. For example, memory 470 of device 400 optionally stores drawing module 480, presentation module 482, word processing module 484, website creation module 486, disk authoring module 488, and/or spreadsheet module 490, while memory 202 of portable multifunction device 200 (FIG. 2A) optionally does not store these modules.


Each of the above-identified elements in FIG. 4 may be stored in one or more of the previously mentioned memory devices. Each of the above-identified modules corresponds to a set of instructions for performing a function described above. The above-identified modules or programs (e.g., sets of instructions) need not be implemented as separate software programs, procedures, or modules, and thus various subsets of these modules may be combined or otherwise rearranged in various embodiments. In some embodiments, memory 470 may store a subset of the modules and data structures identified above. Furthermore, memory 470 may store additional modules and data structures not described above.


Attention is now directed towards embodiments of user interfaces that may be implemented on, for example, portable multifunction device 200.



FIG. 5A illustrates an exemplary user interface for a menu of applications on portable multifunction device 200 in accordance with some embodiments. Similar user interfaces may be implemented on device 400. In some embodiments, user interface 500 includes the following elements, or a subset or superset thereof:


Signal strength indicator(s) 502 for wireless communication(s), such as cellular and Wi-Fi signals;

    • Time 504;
    • Bluetooth indicator 505;
    • Battery status indicator 506;
    • Tray 508 with icons for frequently used applications, such as:
      • Icon 516 for telephone module 238, labeled “Phone,” which optionally includes an indicator 514 of the number of missed calls or voicemail messages;
      • Icon 518 for email client module 240, labeled “Mail,” which optionally includes an indicator 510 of the number of unread emails;
      • Icon 520 for browser module 247, labeled “Browser;” and
      • Icon 522 for video and music player module 252, also referred to as iPod (trademark of Apple Inc.) module 252, labeled “iPod;” and
    • Icons for other applications, such as:
      • Icon 524 for IM module 241, labeled “Messages;”
      • Icon 526 for calendar module 248, labeled “Calendar;”
      • Icon 528 for image management module 244, labeled “Photos;”
      • Icon 530 for camera module 243, labeled “Camera;”
      • Icon 532 for online video module 255, labeled “Online Video;”
      • Icon 534 for stocks widget 249-2, labeled “Stocks;”
      • Icon 536 for map module 254, labeled “Maps;”
      • Icon 538 for weather widget 249-1, labeled “Weather;”
      • Icon 540 for alarm clock widget 249-4, labeled “Clock;”
      • Icon 542 for workout support module 242, labeled “Workout Support;”
      • Icon 544 for notes module 253, labeled “Notes;” and
      • Icon 546 for a settings application or module, labeled “Settings,” which provides access to settings for device 200 and its various applications 236.


It should be noted that the icon labels illustrated in FIG. 5A are merely exemplary. For example, icon 522 for video and music player module 252 may optionally be labeled “Music” or “Music Player.” Other labels are, optionally, used for various application icons. In some embodiments, a label for a respective application icon includes a name of an application corresponding to the respective application icon. In some embodiments, a label for a particular application icon is distinct from a name of an application corresponding to the particular application icon.



FIG. 5B illustrates an exemplary user interface on a device (e.g., device 400, FIG. 4) with a touch-sensitive surface 551 (e.g., a tablet or touchpad 455, FIG. 4) that is separate from the display 550 (e.g., touch screen display 212). Device 400 also, optionally, includes one or more contact intensity sensors (e.g., one or more of sensors 457) for detecting intensity of contacts on touch-sensitive surface 551 and/or one or more tactile output generators 459 for generating tactile outputs for a user of device 400.


Although some of the examples which follow will be given with reference to inputs on touch screen display 212 (where the touch-sensitive surface and the display are combined), in some embodiments, the device detects inputs on a touch-sensitive surface that is separate from the display, as shown in FIG. 5B. In some embodiments, the touch-sensitive surface (e.g., 551 in FIG. 5B) has a primary axis (e.g., 552 in FIG. 5B) that corresponds to a primary axis (e.g., 553 in FIG. 5B) on the display (e.g., 550). In accordance with these embodiments, the device detects contacts (e.g., 560 and 562 in FIG. 5B) with the touch-sensitive surface 551 at locations that correspond to respective locations on the display (e.g., in FIG. 5B, 560 corresponds to 568 and 562 corresponds to 570). In this way, user inputs (e.g., contacts 560 and 562, and movements thereof) detected by the device on the touch-sensitive surface (e.g., 551 in FIG. 5B) are used by the device to manipulate the user interface on the display (e.g., 550 in FIG. 5B) of the multifunction device when the touch-sensitive surface is separate from the display. It should be understood that similar methods are, optionally, used for other user interfaces described herein.


Additionally, while the following examples are given primarily with reference to finger inputs (e.g., finger contacts, finger tap gestures, and/or finger swipe gestures), it should be understood that, in some embodiments, one or more of the finger inputs are replaced with input from another input device (e.g., a mouse-based input or stylus input). For example, a swipe gesture is, optionally, replaced with a mouse click (e.g., instead of a contact) followed by movement of the cursor along the path of the swipe (e.g., instead of movement of the contact). As another example, a tap gesture is, optionally, replaced with a mouse click while the cursor is located over the location of the tap gesture (e.g., instead of detection of the contact followed by ceasing to detect the contact). Similarly, when multiple user inputs are simultaneously detected, it should be understood that multiple computer mice are, optionally, used simultaneously, or a mouse and finger contacts are, optionally, used simultaneously.



FIG. 6A illustrates exemplary personal electronic device 600. Device 600 includes body 602. In some embodiments, device 600 can include some or all of the features described with respect to devices 200 and 400 (e.g., FIGS. 2A and 4). In some embodiments, device 600 has touch-sensitive display screen 604, hereafter touch screen 604. Alternatively, or in addition to touch screen 604, device 600 has a display and a touch-sensitive surface. As with devices 200 and 400, in some embodiments, touch screen 604 (or the touch-sensitive surface) may have one or more intensity sensors for detecting intensity of contacts (e.g., touches) being applied. The one or more intensity sensors of touch screen 604 (or the touch-sensitive surface) can provide output data that represents the intensity of touches. The user interface of device 600 can respond to touches based on their intensity, meaning that touches of different intensities can invoke different user interface operations on device 600.


Techniques for detecting and processing touch intensity may be found, for example, in related applications: International Patent Application Serial No. PCT/US2013/040061, titled “Device, Method, and Graphical User Interface for Displaying User Interface Objects Corresponding to an Application,” filed May 8, 2013, and International Patent Application Serial No. PCT/US2013/069483, titled “Device, Method, and Graphical User Interface for Transitioning Between Touch Input to Display Output Relationships,” filed Nov. 11, 2013, each of which is hereby incorporated by reference in their entirety.


In some embodiments, device 600 has one or more input mechanisms 606 and 608. Input mechanisms 606 and 608, if included, can be physical. Examples of physical input mechanisms include push buttons and rotatable mechanisms. In some embodiments, device 600 has one or more attachment mechanisms. Such attachment mechanisms, if included, can permit attachment of device 600 with, for example, hats, eyewear, earrings, necklaces, shirts, jackets, bracelets, watch straps, chains, trousers, belts, shoes, purses, backpacks, and so forth. These attachment mechanisms may permit device 600 to be worn by a user.



FIG. 6B depicts exemplary personal electronic device 600. In some embodiments, device 600 can include some or all of the components described with respect to FIGS. 2A-2B and 4. Device 600 has bus 612 that operatively couples I/O section 614 with one or more computer processors 616 and memory 618. I/O section 614 can be connected to display 604, which can have touch-sensitive component 622 and, optionally, touch-intensity sensitive component 624. In addition, I/O section 614 can be connected with communication unit 630 for receiving application and operating system data using Wi-Fi, Bluetooth, near field communication (NFC), cellular, and/or other wireless communication techniques. Device 600 can include input mechanisms 606 and/or 608. Input mechanism 606 may be a rotatable input device or a depressible and rotatable input device, for example. Input mechanism 608 may be a button, in some examples.


Input mechanism 608 may be a microphone, in some examples. Personal electronic device 600 can include various sensors, such as GPS sensor 632, accelerometer 634, directional sensor 640 (e.g., compass), gyroscope 636, motion sensor 638, and/or a combination thereof, all of which can be operatively connected to I/O section 614.


Memory 618 of personal electronic device 600 can be a non-transitory computer-readable storage medium, for storing computer-executable instructions, which, when executed by one or more computer processors 616, for example, can cause the computer processors to perform the techniques described below, including process 1200 (FIGS. 12A-12D). The computer-executable instructions can also be stored and/or transported within any non-transitory computer-readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. Personal electronic device 600 is not limited to the components and configuration of FIG. 6B, but can include other or additional components in multiple configurations.


As used here, the term “affordance” refers to a user-interactive graphical user interface object that may be displayed on the display screen of devices 200, 400, and/or 600 (FIGS. 2A, 4, and 6A-6B). For example, an image (e.g., icon), a button, and text (e.g., link) may each constitute an affordance.


As used herein, the term “focus selector” refers to an input element that indicates a current part of a user interface with which a user is interacting. In some implementations that include a cursor or other location marker, the cursor acts as a “focus selector” so that when an input (e.g., a press input) is detected on a touch-sensitive surface (e.g., touchpad 455 in FIG. 4 or touch-sensitive surface 551 in FIG. 5B) while the cursor is over a particular user interface element (e.g., a button, window, slider or other user interface element), the particular user interface element is adjusted in accordance with the detected input. In some implementations that include a touch screen display (e.g., touch-sensitive display system 212 in FIG. 2A or touch screen 212 in FIG. 5A) that enables direct interaction with user interface elements on the touch screen display, a detected contact on the touch screen acts as a “focus selector” so that when an input (e.g., a press input by the contact) is detected on the touch screen display at a location of a particular user interface element (e.g., a button, window, slider, or other user interface element), the particular user interface element is adjusted in accordance with the detected input. In some implementations, focus is moved from one region of a user interface to another region of the user interface without corresponding movement of a cursor or movement of a contact on a touch screen display (e.g., by using a tab key or arrow keys to move focus from one button to another button); in these implementations, the focus selector moves in accordance with movement of focus between different regions of the user interface. Without regard to the specific form taken by the focus selector, the focus selector is generally the user interface element (or contact on a touch screen display) that is controlled by the user so as to communicate the user's intended interaction with the user interface (e.g., by indicating, to the device, the element of the user interface with which the user is intending to interact). For example, the location of a focus selector (e.g., a cursor, a contact, or a selection box) over a respective button while a press input is detected on the touch-sensitive surface (e.g., a touchpad or touch screen) will indicate that the user is intending to activate the respective button (as opposed to other user interface elements shown on a display of the device).


As used in the specification and claims, the term “characteristic intensity” of a contact refers to a characteristic of the contact based on one or more intensities of the contact. In some embodiments, the characteristic intensity is based on multiple intensity samples. The characteristic intensity is, optionally, based on a predefined number of intensity samples, or a set of intensity samples collected during a predetermined time period (e.g., 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10 seconds) relative to a predefined event (e.g., after detecting the contact, prior to detecting liftoff of the contact, before or after detecting a start of movement of the contact, prior to detecting an end of the contact, before or after detecting an increase in intensity of the contact, and/or before or after detecting a decrease in intensity of the contact). A characteristic intensity of a contact is, optionally based on one or more of: a maximum value of the intensities of the contact, a mean value of the intensities of the contact, an average value of the intensities of the contact, a top 10 percentile value of the intensities of the contact, a value at the half maximum of the intensities of the contact, a value at the 90 percent maximum of the intensities of the contact, or the like. In some embodiments, the duration of the contact is used in determining the characteristic intensity (e.g., when the characteristic intensity is an average of the intensity of the contact over time). In some embodiments, the characteristic intensity is compared to a set of one or more intensity thresholds to determine whether an operation has been performed by a user. For example, the set of one or more intensity thresholds may include a first intensity threshold and a second intensity threshold. In this example, a contact with a characteristic intensity that does not exceed the first threshold results in a first operation, a contact with a characteristic intensity that exceeds the first intensity threshold and does not exceed the second intensity threshold results in a second operation, and a contact with a characteristic intensity that exceeds the second threshold results in a third operation. In some embodiments, a comparison between the characteristic intensity and one or more thresholds is used to determine whether or not to perform one or more operations (e.g., whether to perform a respective operation or forgo performing the respective operation) rather than being used to determine whether to perform a first operation or a second operation.


In some embodiments, a portion of a gesture is identified for purposes of determining a characteristic intensity. For example, a touch-sensitive surface may receive a continuous swipe contact transitioning from a start location and reaching an end location, at which point the intensity of the contact increases. In this example, the characteristic intensity of the contact at the end location may be based on only a portion of the continuous swipe contact, and not the entire swipe contact (e.g., only the portion of the swipe contact at the end location). In some embodiments, a smoothing algorithm may be applied to the intensities of the swipe contact prior to determining the characteristic intensity of the contact. For example, the smoothing algorithm optionally includes one or more of: an unweighted sliding-average smoothing algorithm, a triangular smoothing algorithm, a median filter smoothing algorithm, and/or an exponential smoothing algorithm. In some circumstances, these smoothing algorithms eliminate narrow spikes or dips in the intensities of the swipe contact for purposes of determining a characteristic intensity.


The intensity of a contact on the touch-sensitive surface may be characterized relative to one or more intensity thresholds, such as a contact-detection intensity threshold, a light press intensity threshold, a deep press intensity threshold, and/or one or more other intensity thresholds. In some embodiments, the light press intensity threshold corresponds to an intensity at which the device will perform operations typically associated with clicking a button of a physical mouse or a trackpad. In some embodiments, the deep press intensity threshold corresponds to an intensity at which the device will perform operations that are different from operations typically associated with clicking a button of a physical mouse or a trackpad. In some embodiments, when a contact is detected with a characteristic intensity below the light press intensity threshold (e.g., and above a nominal contact-detection intensity threshold below which the contact is no longer detected), the device will move a focus selector in accordance with movement of the contact on the touch-sensitive surface without performing an operation associated with the light press intensity threshold or the deep press intensity threshold. Generally, unless otherwise stated, these intensity thresholds are consistent between different sets of user interface figures.


An increase of characteristic intensity of the contact from an intensity below the light press intensity threshold to an intensity between the light press intensity threshold and the deep press intensity threshold is sometimes referred to as a “light press” input. An increase of characteristic intensity of the contact from an intensity below the deep press intensity threshold to an intensity above the deep press intensity threshold is sometimes referred to as a “deep press” input. An increase of characteristic intensity of the contact from an intensity below the contact-detection intensity threshold to an intensity between the contact-detection intensity threshold and the light press intensity threshold is sometimes referred to as detecting the contact on the touch surface. A decrease of characteristic intensity of the contact from an intensity above the contact-detection intensity threshold to an intensity below the contact-detection intensity threshold is sometimes referred to as detecting liftoff of the contact from the touch-surface. In some embodiments, the contact-detection intensity threshold is zero. In some embodiments, the contact-detection intensity threshold is greater than zero.


In some embodiments described herein, one or more operations are performed in response to detecting a gesture that includes a respective press input or in response to detecting the respective press input performed with a respective contact (or a plurality of contacts), where the respective press input is detected based at least in part on detecting an increase in intensity of the contact (or plurality of contacts) above a press-input intensity threshold. In some embodiments, the respective operation is performed in response to detecting the increase in intensity of the respective contact above the press-input intensity threshold (e.g., a “down stroke” of the respective press input). In some embodiments, the press input includes an increase in intensity of the respective contact above the press-input intensity threshold and a subsequent decrease in intensity of the contact below the press-input intensity threshold, and the respective operation is performed in response to detecting the subsequent decrease in intensity of the respective contact below the press-input threshold (e.g., an “up stroke” of the respective press input).


In some embodiments, the device employs intensity hysteresis to avoid accidental inputs, sometimes termed “jitter,” where the device defines or selects a hysteresis intensity threshold with a predefined relationship to the press-input intensity threshold (e.g., the hysteresis intensity threshold is X intensity units lower than the press-input intensity threshold or the hysteresis intensity threshold is 75%, 90%, or some reasonable proportion of the press-input intensity threshold). Thus, in some embodiments, the press input includes an increase in intensity of the respective contact above the press-input intensity threshold and a subsequent decrease in intensity of the contact below the hysteresis intensity threshold that corresponds to the press-input intensity threshold, and the respective operation is performed in response to detecting the subsequent decrease in intensity of the respective contact below the hysteresis intensity threshold (e.g., an “up stroke” of the respective press input). Similarly, in some embodiments, the press input is detected only when the device detects an increase in intensity of the contact from an intensity at or below the hysteresis intensity threshold to an intensity at or above the press-input intensity threshold and, optionally, a subsequent decrease in intensity of the contact to an intensity at or below the hysteresis intensity, and the respective operation is performed in response to detecting the press input (e.g., the increase in intensity of the contact or the decrease in intensity of the contact, depending on the circumstances).


For ease of explanation, the descriptions of operations performed in response to a press input associated with a press-input intensity threshold or in response to a gesture including the press input are, optionally, triggered in response to detecting either: an increase in intensity of a contact above the press-input intensity threshold, an increase in intensity of a contact from an intensity below the hysteresis intensity threshold to an intensity above the press-input intensity threshold, a decrease in intensity of the contact below the press-input intensity threshold, and/or a decrease in intensity of the contact below the hysteresis intensity threshold corresponding to the press-input intensity threshold. Additionally, in examples where an operation is described as being performed in response to detecting a decrease in intensity of a contact below the press-input intensity threshold, the operation is, optionally, performed in response to detecting a decrease in intensity of the contact below a hysteresis intensity threshold corresponding to, and lower than, the press-input intensity threshold.


3. Digital Assistant System



FIG. 7A illustrates a block diagram of digital assistant system 700 in accordance with various examples. In some examples, digital assistant system 700 can be implemented on a standalone computer system. In some examples, digital assistant system 700 can be distributed across multiple computers. In some examples, some of the modules and functions of the digital assistant can be divided into a server portion and a client portion, where the client portion resides on one or more user devices (e.g., devices 104, 122, 200, 400, or 600) and communicates with the server portion (e.g., server system 108) through one or more networks, e.g., as shown in FIG. 1. In some examples, digital assistant system 700 can be an implementation of server system 108 (and/or DA server 106) shown in FIG. 1. It should be noted that digital assistant system 700 is only one example of a digital assistant system, and that digital assistant system 700 can have more or fewer components than shown, may combine two or more components, or may have a different configuration or arrangement of the components. The various components shown in FIG. 7A can be implemented in hardware, software instructions for execution by one or more processors, firmware, including one or more signal processing and/or application specific integrated circuits, or a combination thereof.


Digital assistant system 700 can include memory 702, one or more processors 704, input/output (I/O) interface 706, and network communications interface 708. These components can communicate with one another over one or more communication buses or signal lines 710.


In some examples, memory 702 can include a non-transitory computer-readable medium, such as high-speed random access memory and/or a non-volatile computer-readable storage medium (e.g., one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid-state memory devices).


In some examples, I/O interface 706 can couple input/output devices 716 of digital assistant system 700, such as displays, keyboards, touch screens, and microphones, to user interface module 722. I/O interface 706, in conjunction with user interface module 722, can receive user inputs (e.g., voice input, keyboard inputs, touch inputs, etc.) and process them accordingly. In some examples, e.g., when the digital assistant is implemented on a standalone user device, digital assistant system 700 can include any of the components and I/O communication interfaces described with respect to devices 200, 400, or 600 in FIGS. 2A, 4, 6A-6B, respectively. In some examples, digital assistant system 700 can represent the server portion of a digital assistant implementation, and can interact with the user through a client-side portion residing on a user device (e.g., devices 104, 200, 400, or 600).


In some examples, the network communications interface 708 can include wired communication port(s) 712 and/or wireless transmission and reception circuitry 714. The wired communication port(s) 712 can receive and send communication signals via one or more wired interfaces, e.g., Ethernet, Universal Serial Bus (USB), FIREWIRE, etc. The wireless circuitry 714 can receive and send RF signals and/or optical signals from/to communications networks and other communications devices. The wireless communications can use any of a plurality of communications standards, protocols, and technologies, such as GSM, EDGE, CDMA, TDMA, Bluetooth, Wi-Fi, VoIP, Wi-MAX, or any other suitable communication protocol. Network communications interface 708 can enable communication between digital assistant system 700 with networks, such as the Internet, an intranet, and/or a wireless network, such as a cellular telephone network, a wireless local area network (LAN), and/or a metropolitan area network (MAN), and other devices.


In some examples, memory 702, or the computer-readable storage media of memory 702, can store programs, modules, instructions, and data structures including all or a subset of: operating system 718, communications module 720, user interface module 722, one or more applications 724, and digital assistant module 726. In particular, memory 702, or the computer-readable storage media of memory 702, can store instructions for performing process 1200, described below. One or more processors 704 can execute these programs, modules, and instructions, and read/write from/to the data structures.


Operating system 718 (e.g., Darwin, RTXC, LINUX, UNIX, iOS, OS X, WINDOWS, or an embedded operating system such as VxWorks) can include various software components and/or drivers for controlling and managing general system tasks (e.g., memory management, storage device control, power management, etc.) and facilitates communications between various hardware, firmware, and software components.


Communications module 720 can facilitate communications between digital assistant system 700 with other devices over network communications interface 708. For example, communications module 720 can communicate with RF circuitry 208 of electronic devices such as devices 200, 400, and 600 shown in FIGS. 2A, 4, 6A-6B, respectively. Communications module 720 can also include various components for handling data received by wireless circuitry 714 and/or wired communications port 712.


User interface module 722 can receive commands and/or inputs from a user via I/O interface 706 (e.g., from a keyboard, touch screen, pointing device, controller, and/or microphone), and generate user interface objects on a display. User interface module 722 can also prepare and deliver outputs (e.g., speech, sound, animation, text, icons, vibrations, haptic feedback, light, etc.) to the user via the I/O interface 706 (e.g., through displays, audio channels, speakers, touch-pads, etc.).


Applications 724 can include programs and/or modules that are configured to be executed by one or more processors 704. For example, if the digital assistant system is implemented on a standalone user device, applications 724 can include user applications, such as games, a calendar application, a navigation application, or an email application. If digital assistant system 700 is implemented on a server, applications 724 can include resource management applications, diagnostic applications, or scheduling applications, for example.


Memory 702 can also store digital assistant module 726 (or the server portion of a digital assistant). In some examples, digital assistant module 726 can include the following sub-modules, or a subset or superset thereof: input/output processing module 728, speech-to-text (STT) processing module 730, natural language processing module 732, dialogue flow processing module 734, task flow processing module 736, service processing module 738, and speech synthesis module 740. Each of these modules can have access to one or more of the following systems or data and models of the digital assistant module 726, or a subset or superset thereof: ontology 760, vocabulary index 744, user data 748, task flow models 754, service models 756, and ASR systems 731.


In some examples, using the processing modules, data, and models implemented in digital assistant module 726, the digital assistant can perform at least some of the following: converting speech input into text; identifying a user's intent expressed in a natural language input received from the user; actively eliciting and obtaining information needed to fully infer the user's intent (e.g., by disambiguating words, games, intentions, etc.); determining the task flow for fulfilling the inferred intent; and executing the task flow to fulfill the inferred intent.


In some examples, as shown in FIG. 7B, I/O processing module 728 can interact with the user through I/O devices 716 in FIG. 7A or with a user device (e.g., devices 104, 200, 400, or 600) through network communications interface 708 in FIG. 7A to obtain user input (e.g., a speech input) and to provide responses (e.g., as speech outputs) to the user input. I/O processing module 728 can optionally obtain contextual information associated with the user input from the user device, along with or shortly after the receipt of the user input. The contextual information can include user-specific data, vocabulary, and/or preferences relevant to the user input. In some examples, the contextual information also includes software and hardware states of the user device at the time the user request is received, and/or information related to the surrounding environment of the user at the time that the user request was received. In some examples, I/O processing module 728 can also send follow-up questions to, and receive answers from, the user regarding the user request. When a user request is received by I/O processing module 728 and the user request can include speech input, I/O processing module 728 can forward the speech input to STT processing module 730 (or a speech recognizer) for speech-to-text conversions.


STT processing module 730 can include one or more ASR systems. The one or more ASR systems can process the speech input that is received through I/O processing module 728 to produce a recognition result. Each ASR system can include a front-end speech pre-processor. The front-end speech pre-processor can extract representative features from the speech input. For example, the front-end speech pre-processor can perform a Fourier transform on the speech input to extract spectral features that characterize the speech input as a sequence of representative multi-dimensional vectors. Further, each ASR system can include one or more speech recognition models (e.g., acoustic models and/or language models) and can implement one or more speech recognition engines. Examples of speech recognition models can include Hidden Markov Models, Gaussian-Mixture Models, Deep Neural Network Models, n-gram language models, and other statistical models. Examples of speech recognition engines can include the dynamic time warping based engines and weighted finite-state transducers (WFST) based engines. The one or more speech recognition models and the one or more speech recognition engines can be used to process the extracted representative features of the front-end speech pre-processor to produce intermediate recognitions results (e.g., phonemes, phonemic strings, and sub-words), and ultimately, text recognition results (e.g., words, word strings, or sequence of tokens). In some examples, the speech input can be processed at least partially by a third-party service or on the user's device (e.g., device 104, 200, 400, or 600) to produce the recognition result. Once STT processing module 730 produces recognition results containing a text string (e.g., words, or sequence of words, or sequence of tokens), the recognition result can be passed to natural language processing module 732 for intent deduction.


More details on the speech-to-text processing are described in U.S. Utility application Ser. No. 13/236,942 for “Consolidating Speech Recognition Results,” filed on Sep. 20, 2011, the entire disclosure of which is incorporated herein by reference.


In some examples, STT processing module 730 can include and/or access a vocabulary of recognizable words via phonetic alphabet conversion module 731. Each vocabulary word can be associated with one or more candidate pronunciations of the word represented in a speech recognition phonetic alphabet. In particular, the vocabulary of recognizable words can include a word that is associated with a plurality of candidate pronunciations. For example, the vocabulary may include the word “tomato” that is associated with the candidate pronunciations of /custom character/ and /custom character/. Further, vocabulary words can be associated with custom candidate pronunciations that are based on previous speech inputs from the user. Such custom candidate pronunciations can be stored in STT processing module 730 and can be associated with a particular user via the user's profile on the device. In some examples, the candidate pronunciations for words can be determined based on the spelling of the word and one or more linguistic and/or phonetic rules. In some examples, the candidate pronunciations can be manually generated, e.g., based on known canonical pronunciations.


In some examples, the candidate pronunciations can be ranked based on the commonness of the candidate pronunciation. For example, the candidate pronunciation /custom character/ can be ranked higher than /custom character/, because the former is a more commonly used pronunciation (e.g., among all users, for users in a particular geographical region, or for any other appropriate subset of users). In some examples, candidate pronunciations can be ranked based on whether the candidate pronunciation is a custom candidate pronunciation associated with the user. For example, custom candidate pronunciations can be ranked higher than canonical candidate pronunciations. This can be useful for recognizing proper nouns having a unique pronunciation that deviates from canonical pronunciation. In some examples, candidate pronunciations can be associated with one or more speech characteristics, such as geographic origin, nationality, or ethnicity. For example, the candidate pronunciation /custom character/ can be associated with the United States, whereas the candidate pronunciation /custom character/ can be associated with Great Britain. Further, the rank of the candidate pronunciation can be based on one or more characteristics (e.g., geographic origin, nationality, ethnicity, etc.) of the user stored in the user's profile on the device. For example, it can be determined from the user's profile that the user is associated with the United States. Based on the user being associated with the United States, the candidate pronunciation /custom character/ (associated with the United States) can be ranked higher than the candidate pronunciation /custom character/ (associated with Great Britain). In some examples, one of the ranked candidate pronunciations can be selected as a predicted pronunciation (e.g., the most likely pronunciation).


When a speech input is received, STT processing module 730 can be used to determine the phonemes corresponding to the speech input (e.g., using an acoustic model), and then attempt to determine words that match the phonemes (e.g., using a language model). For example, if STT processing module 730 can first identify the sequence of phonemes /custom character/ corresponding to a portion of the speech input, it can then determine, based on vocabulary index 744, that this sequence corresponds to the word “tomato.”


In some examples, STT processing module 730 can use approximate matching techniques to determine words in a voice input. Thus, for example, the STT processing module 730 can determine that the sequence of phonemes /custom character/ corresponds to the word “tomato,” even if that particular sequence of phonemes is not one of the candidate sequence of phonemes for that word.


Natural language processing module 732 (“natural language processor”) of the digital assistant can take the sequence of words or tokens (“token sequence”) generated by STT processing module 730 and attempt to associate the token sequence with one or more “actionable intents” recognized by the digital assistant. An “actionable intent” can represent a task that can be performed by the digital assistant and can have an associated task flow implemented in task flow models 754. The associated task flow can be a series of programmed actions and steps that the digital assistant takes in order to perform the task. The scope of a digital assistant's capabilities can be dependent on the number and variety of task flows that have been implemented and stored in task flow models 754 or, in other words, on the number and variety of “actionable intents” that the digital assistant recognizes. The effectiveness of the digital assistant, however, can also be dependent on the assistant's ability to infer the correct “actionable intent(s)” from the user request expressed in natural language.


In some examples, in addition to the sequence of words or tokens obtained from STT processing module 730, natural language processing module 732 can also receive contextual information associated with the user request, e.g., from I/O processing module 728. The natural language processing module 732 can optionally use the contextual information to clarify, supplement, and/or further define the information contained in the token sequence received from STT processing module 730. The contextual information can include, for example, user preferences, hardware and/or software states of the user device, sensor information collected before, during, or shortly after the user request, prior interactions (e.g., dialogue) between the digital assistant and the user, and the like. As described herein, contextual information can be dynamic, and can change with time, location, content of the dialogue, and other factors.


In some examples, the natural language processing can be based on, e.g., ontology 760. Ontology 760 can be a hierarchical structure containing many nodes, each node representing either an “actionable intent” or a “property” relevant to one or more of the “actionable intents” or other “properties.” As noted above, an “actionable intent” can represent a task that the digital assistant is capable of performing, i.e., it is “actionable” or can be acted on. A “property” can represent a parameter associated with an actionable intent or a sub-aspect of another property. A linkage between an actionable intent node and a property node in ontology 760 can define how a parameter represented by the property node pertains to the task represented by the actionable intent node.


In some examples, ontology 760 can be made up of actionable intent nodes and property nodes. Within ontology 760, each actionable intent node can be linked to one or more property nodes either directly or through one or more intermediate property nodes. Similarly, each property node can be linked to one or more actionable intent nodes either directly or through one or more intermediate property nodes. For example, as shown in FIG. 7C, ontology 760 can include a “restaurant reservation” node (i.e., an actionable intent node). Property nodes “restaurant,” “date/time” (for the reservation), and “party size” can each be directly linked to the actionable intent node (i.e., the “restaurant reservation” node).


In addition, property nodes “cuisine,” “price range,” “phone number,” and “location” can be sub-nodes of the property node “restaurant,” and can each be linked to the “restaurant reservation” node (i.e., the actionable intent node) through the intermediate property node “restaurant.” For another example, as shown in FIG. 7C, ontology 760 can also include a “set reminder” node (i.e., another actionable intent node). Property nodes “date/time” (for setting the reminder) and “subject” (for the reminder) can each be linked to the “set reminder” node. Since the property “date/time” can be relevant to both the task of making a restaurant reservation and the task of setting a reminder, the property node “date/time” can be linked to both the “restaurant reservation” node and the “set reminder” node in ontology 760.


An actionable intent node, along with its linked concept nodes, can be described as a “domain.” In the present discussion, each domain can be associated with a respective actionable intent and refers to the group of nodes (and the relationships there between) associated with the particular actionable intent. For example, ontology 760 shown in FIG. 7C can include an example of restaurant reservation domain 762 and an example of reminder domain 764 within ontology 760. The restaurant reservation domain includes the actionable intent node “restaurant reservation,” property nodes “restaurant,” “date/time,” and “party size,” and sub-property nodes “cuisine,” “price range,” “phone number,” and “location.” Reminder domain 764 can include the actionable intent node “set reminder,” and property nodes “subject” and “date/time.” In some examples, ontology 760 can be made up of many domains. Each domain can share one or more property nodes with one or more other domains. For example, the “date/time” property node can be associated with many different domains (e.g., a scheduling domain, a travel reservation domain, a movie ticket domain, etc.), in addition to restaurant reservation domain 762 and reminder domain 764.


While FIG. 7C illustrates two example domains within ontology 760, other domains can include, for example, “find a movie,” “initiate a phone call,” “find directions,” “schedule a meeting,” “send a message,” and “provide an answer to a question,” “read a list,” “providing navigation instructions,” “provide instructions for a task,” and so on. A “send a message” domain can be associated with a “send a message” actionable intent node, and may further include property nodes such as “recipient(s),” “message type,” and “message body.” The property node “recipient” can be further defined, for example, by the sub-property nodes such as “recipient name” and “message address.”


In some examples, ontology 760 can include all the domains (and hence actionable intents) that the digital assistant is capable of understanding and acting upon. In some examples, ontology 760 can be modified, such as by adding or removing entire domains or nodes, or by modifying relationships between the nodes within the ontology 760.


In some examples, nodes associated with multiple related actionable intents can be clustered under a “super domain” in ontology 760. For example, a “travel” super-domain can include a cluster of property nodes and actionable intent nodes related to travel. The actionable intent nodes related to travel can include “airline reservation,” “hotel reservation,” “car rental,” “get directions,” “find points of interest,” and so on. The actionable intent nodes under the same super domain (e.g., the “travel” super domain) can have many property nodes in common. For example, the actionable intent nodes for “airline reservation,” “hotel reservation,” “car rental,” “get directions,” and “find points of interest” can share one or more of the property nodes “start location,” “destination,” “departure date/time,” “arrival date/time,” and “party size.”


In some examples, each node in ontology 760 can be associated with a set of words and/or phrases that are relevant to the property or actionable intent represented by the node. The respective set of words and/or phrases associated with each node can be the so-called “vocabulary” associated with the node. The respective set of words and/or phrases associated with each node can be stored in vocabulary index 744 in association with the property or actionable intent represented by the node. For example, returning to FIG. 7B, the vocabulary associated with the node for the property of “restaurant” can include words such as “food,” “drinks,” “cuisine,” “hungry,” “eat,” “pizza,” “fast food,” “meal,” and so on. For another example, the vocabulary associated with the node for the actionable intent of “initiate a phone call” can include words and phrases such as “call,” “phone,” “dial,” “ring,” “call this number,” “make a call to,” and so on. The vocabulary index 744 can optionally include words and phrases in different languages.


Natural language processing module 732 can receive the token sequence (e.g., a text string) from STT processing module 730, and determine what nodes are implicated by the words in the token sequence. In some examples, if a word or phrase in the token sequence is found to be associated with one or more nodes in ontology 760 (via vocabulary index 744), the word or phrase can “trigger” or “activate” those nodes. Based on the quantity and/or relative importance of the activated nodes, natural language processing module 732 can select one of the actionable intents as the task that the user intended the digital assistant to perform. In some examples, the domain that has the most “triggered” nodes can be selected. In some examples, the domain having the highest confidence value (e.g., based on the relative importance of its various triggered nodes) can be selected. In some examples, the domain can be selected based on a combination of the number and the importance of the triggered nodes. In some examples, additional factors are considered in selecting the node as well, such as whether the digital assistant has previously correctly interpreted a similar request from a user.


User data 748 can include user-specific information, such as user-specific vocabulary, user preferences, user address, user's default and secondary languages, user's contact list, and other short-term or long-term information for each user. In some examples, natural language processing module 732 can use the user-specific information to supplement the information contained in the user input to further define the user intent. For example, for a user request “invite my friends to my birthday party,” natural language processing module 732 can be able to access user data 748 to determine who the “friends” are and when and where the “birthday party” would be held, rather than requiring the user to provide such information explicitly in his/her request.


Other details of searching an ontology based on a token string is described in U.S. Utility application Ser. No. 12/341,743 for “Method and Apparatus for Searching Using An Active Ontology,” filed Dec. 22, 2008, the entire disclosure of which is incorporated herein by reference.


In some examples, once natural language processing module 732 identifies an actionable intent (or domain) based on the user request, natural language processing module 732 can generate a structured query to represent the identified actionable intent. In some examples, the structured query can include parameters for one or more nodes within the domain for the actionable intent, and at least some of the parameters are populated with the specific information and requirements specified in the user request. For example, the user may say “Make me a dinner reservation at a sushi place at 7.” In this case, natural language processing module 732 can be able to correctly identify the actionable intent to be “restaurant reservation” based on the user input. According to the ontology, a structured query for a “restaurant reservation” domain may include parameters such as {Cuisine}, {Time}, {Date}, {Party Size}, and the like. In some examples, based on the speech input and the text derived from the speech input using STT processing module 730, natural language processing module 732 can generate a partial structured query for the restaurant reservation domain, where the partial structured query includes the parameters {Cuisine=“Sushi”} and {Time=“7 pm”}. However, in this example, the user's speech input contains insufficient information to complete the structured query associated with the domain. Therefore, other necessary parameters such as {Party Size} and {Date} may not be specified in the structured query based on the information currently available. In some examples, natural language processing module 732 can populate some parameters of the structured query with received contextual information. For example, in some examples, if the user requested a sushi restaurant “near me,” natural language processing module 732 can populate a {location} parameter in the structured query with GPS coordinates from the user device.


In some examples, natural language processing module 732 can pass the generated structured query (including any completed parameters) to task flow processing module 736 (“task flow processor”). Task flow processing module 736 can be configured to receive the structured query from natural language processing module 732, complete the structured query, if necessary, and perform the actions required to “complete” the user's ultimate request. In some examples, the various procedures necessary to complete these tasks can be provided in task flow models 754. In some examples, task flow models 754 can include procedures for obtaining additional information from the user and task flows for performing actions associated with the actionable intent.


As described above, in order to complete a structured query, task flow processing module 736 may need to initiate additional dialogue with the user in order to obtain additional information, and/or disambiguate potentially ambiguous speech inputs. When such interactions are necessary, task flow processing module 736 can invoke dialogue flow processing module 734 to engage in a dialogue with the user. In some examples, dialogue flow processing module 734 can determine how (and/or when) to ask the user for the additional information and receive and processes the user responses. The questions can be provided to and answers can be received from the users through I/O processing module 728. In some examples, dialogue flow processing module 734 can present dialogue output to the user via audio and/or visual output, and receive input from the user via spoken or physical (e.g., clicking) responses. Continuing with the example above, when task flow processing module 736 invokes dialogue flow processing module 734 to determine the “party size” and “date” information for the structured query associated with the domain “restaurant reservation,” dialogue flow processing module 734 can generate questions such as “For how many people?” and “On which day?” to pass to the user. Once answers are received from the user, dialogue flow processing module 734 can then populate the structured query with the missing information or pass the information to task flow processing module 736 to complete the missing information from the structured query.


Once task flow processing module 736 has completed the structured query for an actionable intent, task flow processing module 736 can proceed to perform the ultimate task associated with the actionable intent. Accordingly, task flow processing module 736 can execute the steps and instructions in the task flow model according to the specific parameters contained in the structured query. For example, the task flow model for the actionable intent of “restaurant reservation” can include steps and instructions for contacting a restaurant and actually requesting a reservation for a particular party size at a particular time. For example, using a structured query such as: {restaurant reservation, restaurant=ABC Café, date=3/12/2012, time=7 pm, party size=5}, task flow processing module 736 can perform the steps of: (1) logging onto a server of the ABC Café or a restaurant reservation system such as OPENTABLE®; (2) entering the date, time, and party size information in a form on the website; (3) submitting the form; and (4) making a calendar entry for the reservation in the user's calendar.


In some examples, task flow processing module 736 can employ the assistance of service processing module 738 (“service processing module”) to complete a task requested in the user input or to provide an informational answer requested in the user input. For example, service processing module 738 can act on behalf of task flow processing module 736 to make a phone call, set a calendar entry, invoke a map search, invoke or interact with other user applications installed on the user device, and invoke or interact with third-party services (e.g., a restaurant reservation portal, a social networking website, a banking portal, etc.). In some examples, the protocols and application programming interfaces (API) required by each service can be specified by a respective service model among service models 756. Service processing module 738 can access the appropriate service model for a service and generate requests for the service in accordance with the protocols and APIs required by the service according to the service model.


For example, if a restaurant has enabled an online reservation service, the restaurant can submit a service model specifying the necessary parameters for making a reservation and the APIs for communicating the values of the necessary parameter to the online reservation service. When requested by task flow processing module 736, service processing module 738 can establish a network connection with the online reservation service using the web address stored in the service model and send the necessary parameters of the reservation (e.g., time, date, party size) to the online reservation interface in a format according to the API of the online reservation service.


In some examples, natural language processing module 732, dialogue flow processing module 734, and task flow processing module 736 can be used collectively and iteratively to infer and define the user's intent, obtain information to further clarify and refine the user intent, and finally generate a response (i.e., an output to the user, or the completion of a task) to fulfill the user's intent. The generated response can be a dialogue response to the speech input that at least partially fulfills the user's intent. Further, in some examples, the generated response can be output as a speech output. In these examples, the generated response can be sent to speech synthesis module 740 (e.g., speech synthesizer) where it can be processed to synthesize the dialogue response in speech form. In yet other examples, the generated response can be data content relevant to satisfying a user request in the speech input.


Speech synthesis module 740 can be configured to synthesize speech outputs for presentation to the user. Speech synthesis module 740 synthesizes speech outputs based on text provided by the digital assistant. For example, the generated dialogue response can be in the form of a text string. Speech synthesis module 740 can convert the text string to an audible speech output. Speech synthesis module 740 can use any appropriate speech synthesis technique in order to generate speech outputs from text, including, but not limited to, concatenative synthesis, unit selection synthesis, diphone synthesis, domain-specific synthesis, formant synthesis, articulatory synthesis, hidden Markov model (HMM) based synthesis, and sinewave synthesis. In some examples, speech synthesis module 740 can be configured to synthesize individual words based on phonemic strings corresponding to the words. For example, a phonemic string can be associated with a word in the generated dialogue response. The phonemic string can be stored in metadata associated with the word. Speech synthesis model 740 can be configured to directly process the phonemic string in the metadata to synthesize the word in speech form.


In some examples, instead of (or in addition to) using speech synthesis module 740, speech synthesis can be performed on a remote device (e.g., the server system 108), and the synthesized speech can be sent to the user device for output to the user. For example, this can occur in some implementations where outputs for a digital assistant are generated at a server system. And because server systems generally have more processing power or resources than a user device, it can be possible to obtain higher quality speech outputs than would be practical with client-side synthesis.


Additional details on digital assistants can be found in the U.S. Utility application Ser. No. 12/987,982, entitled “Intelligent Automated Assistant,” filed Jan. 10, 2011, and U.S. Utility application Ser. No. 13/251,088, entitled “Generating and Processing Task Items That Represent Tasks to Perform,” filed Sep. 30, 2011, the entire disclosures of which are incorporated herein by reference.


4. Exemplary Functions of a Digital Assistant—Intelligent Search and Object Management



FIGS. 8A-8F, 9A-9H, 10A-10B, 11A-11D, 12A-12D, and 13A-13C illustrate functionalities of performing a task using a search process or an object managing process by a digital assistant. In some examples, the digital assistant system (e.g., digital assistant system 700) is implemented by a user device according to various examples. In some examples, the user device, a server (e.g., server 108), or a combination thereof, may implement a digital assistant system (e.g., digital assistant system 700). The user device can be implemented using, for example, device 104, 200, or 400. In some examples, the user device is a laptop computer, a desktop computer, or a tablet computer. The user device can operate in a multi-tasking environment, such as a desktop environment.


With references to FIGS. 8A-8F, 9A-9H, 10A-10B, 11A-11D, 12A-12D, and 13A-13C, in some examples, a user device provides various user interfaces (e.g., user interfaces 810, 910, 1010, 1110, 1210, and 1310). The user device displays the various user interfaces on a display (e.g., touch-sensitive display system 212, display 440) associated with the user device. The various user interfaces provide one or more affordances representing different processes (e.g., affordances 820, 920, 1020, 1120, 1220, and 1320 representing searching processes; and affordances 830, 930, 1030, 1130, 1230, and 1330 representing object managing processes). The one or more processes can be instantiated directly or indirectly by the user. For example, a user instantiates the one or more processes by selecting the affordances using an input device such as a keyboard, a mouse, a joystick, a finger, or the like. A user can also instantiate the one or more processes using a speech input, as described in more detail below. Instantiating a process includes invoking the process if the process is not already executing. If at least one instance of the process is executing, instantiating a process includes executing an existing instance of the process or generating a new instance of the process. For example, instantiating an object managing process includes invoking the object managing process, using an existing object managing process, or generate a new instance of the object managing process.


As shown in FIGS. 8A-8F, 9A-9H, 10A-10B, 11A-11D, 12A-12D, and 13A-13C, the user device displays, on a user interface (e.g., user interface 810, 910, 1010, 1110, 1210, and 1310) an affordance (e.g., affordance 840, 940, 1040, 1140, 1240, and 1340) to instantiate a digital assistant service. The affordance can be, for example, a microphone icon representing the digital assistant. The affordance can be displayed at any location on the user interfaces. For example, the affordance can be displayed on the dock (e.g., dock 808, 908, 1008, 1108, 1208, and 1308) at the bottom of the user interfaces, on the menu bar (e.g. menu bar 806, 906, 1006, 1106, 1206, and 1306) at the top of the user interfaces, in a notification center at the right side of the user interfaces, or the like. The affordance can also be displayed dynamically on the user interface. For example, the user device displays the affordance near an application user interface (e.g., an application window) such that the digital assistant service can be conveniently instantiated.


In some examples, the digital assistant is instantiated in response to receiving a pre-determined phrase. For example, the digital assistant is invoked in response to receiving a phrase such as “Hey, Assistant,” “Wake up, Assistant,” “Listen up, Assistant,” “OK, Assistant,” or the like. In some examples, the digital assistant is instantiated in response to receiving a selection of the affordance. For example, a user selects affordance 840, 940, 1040, 1140, 1240, and/or 1340 using an input device such as a mouse, a stylus, a finger, or the like. Providing a digital assistant on a user device consumes computing resources (e.g., power, network bandwidth, memory, and processor cycles). In some examples, the digital assistant is suspended or shut down until a user invokes it. In some examples, the digital assistant is active for various periods of time. For example, the digital assistant can be active and monitoring the user's speech input during the time that various user interfaces are displayed, that the user device is turned on, that the user device is hibernating or sleeping, that the user is logged off, or a combination thereof.


With reference to FIGS. 8A-8F, 9A-9H, 10A-10B, 11A-11D, 12A-12D, and 13A-13C, a digital assistant receives one or more speech inputs, such as speech inputs 852, 854, 855, 856, 952, 954, 1052, 1054, 1152, 1252, or 1352, from a user. The user provides various speech inputs for the purpose of, for example, performing a task using a searching process or an object managing process. In some examples, the digital assistant receives speech inputs directly from the user at the user device or indirectly through another electronic device that is communicatively connected to the user device. The digital assistant receives speech inputs directly from the user via, for example, a microphone (e.g., microphone 213) of the user device. The user device includes a device that is configured to operate in a multi-tasking environment, such as a laptop computer, a desktop computer, a tablet, a server, or the like. The digital assistant can also receive speech inputs indirectly through one or more electronic devices such as a headset, a smartphone, a tablet, or the like. For instance, the user may speak to a headset (not shown). The headset receives the speech input from the user and transmits the speech input or a representation of it to the digital assistant of the user device via, for example, a Bluetooth connection between the headset and the user device.


With reference to FIGS. 8A-8F, 9A-9H, 10A-10B, 11A-11D, 12A-12D, and 13A-13C, in some embodiments, the digital assistant (e.g., represented by affordance 840, 940, 1040, 1140, 1240, and 1340) identifies context information associated with the user device. The context information includes, for example, user-specific data, metadata associated with one or more objects, sensor data, and user device configuration data. An object can be a target or a component of a process (e.g., an object managing process) associated with performing a task or a graphical element currently displayed on screen, and the object or graphical element may have or may not currently have focus (e.g., be currently selected). For example, an object can include a file (e.g., a photo, a document), a folder, a communication (e.g., an email, a message, a notification, or a voicemail), a contact, a calendar, an application, an online resource, or the like. In some examples, the user-specific data includes log information, user preferences, the history of user's interaction with the user device, or the like. Log information indicates recent objects (e.g., a presentation file) used in a process. In some examples, metadata associated with one or more objects includes the title of the object, the time information of the object, the author of the object, the summary of the object, or the like. In some examples, the sensor data includes various data collected by a sensor associated with the user device. For example, the sensor data includes location data indicating the physical location of the user device. In some examples, the user device configuration data includes the current device configurations. For example, the device configurations indicate that the user device is communicatively connected to one or more electronic devices such as a smartphone, a tablet, or the like. As described in more detail below, the user device can perform one or more processes using the context information.


With reference to FIGS. 8A-8F, 9A-9H, 10A-10B, 11A-11D, 12A-12D, and 13A-13C, in response to receiving a speech input, the digital assistant determines a user intent based on the speech input. As described above, in some examples, the digital assistant processes a speech input via an I/O processing module (e.g., I/O processing module 728 as shown in FIG. 7B), an STT processing module (e.g., STT processing module 730 as shown in FIG. 7B), and a natural language processing module (e.g., natural language processing module 732 as shown in FIG. 7B). The I/O processing module forwards the speech input to an STT processing module (or a speech recognizer) for speech-to-text conversions. The speech-to-text conversion generates text based on the speech input. As described above, the STT processing module generates a sequence of words or tokens (“token sequence”) and provides the token sequence to the natural language processing module. The natural language processing module performs natural language processing of the text and determines the user intent based on a result of the natural language processing. For example, the natural language processing module may attempt to associate the token sequence with one or more actionable intents recognized by the digital assistant. As described, once the natural language processing module identifies an actionable intent based on the user input, it generates a structured query to represent the identified actionable intent. The structured query includes one or more parameters associated with the actionable intent. The one or more parameters are used to facilitate the performance of a task based on the actionable intent.


In some embodiments, the digital assistant further determines whether the user intent is to perform a task using a searching process or an object managing process. The searching process is configured to search data stored internally or externally to the user device. The object managing process is configured to manage objects associated with the user device. Various examples of determination of the user intent are provided below in more detail with respect to FIGS. 8A-8F, 9A-9H, 10A-10B, 11A-11D, 12A-12D, and 13A-13C.


With reference to FIG. 8A, in some examples, a user device receives a speech input 852 from a user to instantiate the digital assistant. Speech input 852 includes, for example, “Hey, Assistant.” In response to the speech input, the user device instantiates the digital assistant represented by affordance 840 or 841 such that the digital assistant is actively monitoring subsequent speech inputs. In some examples, the digital assistant provides a spoken output 872 indicating that it is instantiated. For example, spoken output 872 includes “Go ahead, I am listening.” In some examples, the user device receives a selection of affordance 840 or affordance 841 from the user to instantiate the digital assistant. The selection of affordance is performed by using an input device such as a mouse, a stylus, a finger, or the like.


With reference to FIG. 8B, in some examples, the digital assistant receives a speech input 854. Speech input 854 includes, for example, “Open the searching process and find the AAPL stock price today,” or simply “show me the AAPL stock price today.” Based on speech input 854, the digital assistant determines the user intent. For example, to determine the user intent, the digital assistant determines that the actionable intent is obtaining online information and that one or more parameters associated with this actionable intent include “AAPL stock price,” and “today.”


As described, in some examples, the digital assistant further determines whether the user intent is to perform a task using a searching process or an object managing process. In some embodiments, to make the determination, the digital assistant determines whether the speech input includes one or more keywords representing the searching process or the object managing process. For example, the digital assistant determines that speech input 854 includes keywords or a phrase such as “open the searching process,” indicating the user intent is to use the searching process to perform the task. As a result, the digital assistant determines that the user intent is to perform a task using the searching process.


As shown in FIG. 8B, in accordance with a determination the user intent is to perform the task using the searching process, the digital assistant performs the task using the searching process. As described, the natural language processing module of the digital assistant generates a structured query based on the user intent and passes the generated structured query to a task flow processing module (e.g., task flow processing module 736). The task flow processing module receives the structured query from the natural language processing module, completes the structured query, if necessary, and performs the actions required to “complete” the user's ultimate request. Performing the task using the searching process includes, for example, searching at least one object. In some embodiments, at least one object includes a folder, a file (e.g., a photo, an audio, a video), a communication (e.g., an email, a message, a notification, a voicemail), a contact, a calendar, an application (e.g., Keynote, Number, iTunes, Safari), an online informational source (e.g., Google, Yahoo, Bloomberg), or a combination thereof. In some examples, searching an object is based on metadata associated with the object. For example, the searching of a file or folder can use metadata such as a tag, a date, a time, an author, a title, a type of the file, a size, a page count, and/or a file location associated with the folder or file. In some examples, the file or folder is stored internally or externally to the user device. For example, the file or folder can be stored on the hard disk of the user device or stored on a cloud server. In some examples, searching a communication is based on metadata associated with the communication. For example, the searching of an email uses metadata such as the sender of the email, the receiver of the email, the sent/receive dates of the email, or the like.


As illustrated in FIG. 8B, in accordance with the determination that the user intent is to obtain the AAPL stock price using the searching process, the digital assistant performs the searching. For example, the digital assistant instantiates a searching process, represented by affordance 820, and causes the searching process to search today's AAPL stock price. In some examples, the digital assistant further causes the searching process to display a user interface 822 (e.g., a snippet or a window) providing text corresponding to speech input 854 (e.g., “Open the searching process and find the AAPL stock price today”).


With reference to FIG. 8C, in some embodiments, the digital assistant provides a response based on a result of performing the task using the searching process. As illustrated in FIG. 8C, as a result of searching the AAPL stock price, the digital assistant displays a user interface 824 (e.g., a snippet or a window) providing the result of performing the task using the searching process. In some embodiments, user interface 824 is located within user interface 822 as a separate user interface. In some embodiments, user interfaces 824 and 822 are integrated together as a single user interface. On user interface 824, the search result of the stock price of AAPL is displayed. In some embodiments, user interface 824 further provides affordances 831 and 833. Affordance 831 enables closing of user interface 824. For example, if the digital assistant receives a user's selection of affordance 831, user interface 824 disappears or closes from the display of the user device. Affordance 833 enables moving or sharing of the search result displayed on user interface 824. For example, if the digital assistant receives the user's selection of affordance 833, it instantiates a process (e.g., the object managing process) to move or share user interface 824 (or the search result thereof) with a notification application. As shown in FIG. 8C, the digital assistant displays a user interface 826 that is associated with the notification application to provide the search result of AAPL stock price. In some embodiments, user interface 826 displays an affordance 827. Affordance 827 enables scrolling within user interface 826 such that the user can view the entire content (e.g., multiple notifications) within user interface 826 and/or indicates that relative position of the document with respect to its entire length and/or width. In some embodiments, user interface 826 displays results and/or dialog history (e.g., search results obtained from a current and/or past searching process) stored by the digital assistant. Further, in some examples, results of the performance the task are dynamically updated over time. For example, the AAPL stock price can be dynamically updated over time and displayed on user interface 826.


In some embodiments, the digital assistant also provides a spoken output corresponding to the search result. For example, the digital assistant (e.g., represented by affordance 840) provides a spoken output 874 including “Today's AAPL price is $100.00.” In some examples, user interface 822 includes text corresponding to spoken output 874.


With reference to FIG. 8D, in some examples, the digital assistant instantiates a process (e.g., the object managing process) to move or share the search result displayed on user interface 824 in response to a subsequent speech input. For example, the digital assistant receives a speech input 855 such as “Copy the AAPL stock price to my notes.” In response, the digital assistant instantiates a process to move or copy the search result (e.g., the AAPL stock price) to the user's note. As shown in FIG. 8D, in some examples, the digital assistant further displays a user interface 825 providing the copied or moved search result in user's note. In some examples, the digital assistant further provides a spoken output 875 such as “OK, the AAPL stock price is copied to your notes.” In some examples, user interface 822 includes text corresponding to spoken output 875.


With reference to FIG. 8E, in some examples, the digital assistant determines that the user intent is to perform a task using the object managing process and performs the task using an object managing process. For example, the digital assistant receives a speech input 856 such as “Open the object managing process and show me all the photos from my Colorado trip,” or simply “Show me all the photos from my Colorado trip.” Based on speech input 856 and context information, the digital assistant determines the user intent. For example, the digital assistant determines that the actionable intent is to display photos and determines one or more parameters such as “all,” and “Colorado trip.” The digital assistant further determines which photos correspond to the user's Colorado trip using context information. As described, context information includes user-specific data, metadata of one or more objects, sensor data, and/or device configuration data. As an example, metadata associated with one or more files (e.g., file 1, file 2, and file 3 displayed in user interface 832) indicates that the file names includes the word “Colorado” or a city name of Colorado (e.g., “Denver”). The metadata may also indicate that a folder name includes the word “Colorado” or a city name of Colorado (e.g., “Denver”). As another example, sensor data (e.g., GPS data) indicates that the user was travelling within Colorado during a certain period of time. As a result, any photos the user took during that particular period of time are photos taken during the user's Colorado trip. As well, photos themselves may include geotagged metadata that associates the photo with the location at which it was taken. Based on the context information, the digital assistant determines that the user intent is to, for example, display photos stored in a folder having a folder name “Colorado trip,” or display photos taken during the period of time that the user was travelling within Colorado.


As described, in some examples, the digital assistant determines whether the user intent is to perform a task using a searching process or an object managing process. To make such determination, the digital assistant determines whether the speech input includes one or more keywords representing the searching process or the object managing process. For example, the digital assistant determines that speech input 856 includes keywords or a phrase such as “open the object managing process,” indicating that the user intent is to use the object managing process to perform the task.


In accordance with a determination the user intent is to perform the task using the object managing process, the digital assistant performs the task using the object managing process. For example, the digital assistant searches at least one object using the object managing process. In some examples, at least one object includes at least one of a folder or a file. A file can include at least one of a photo, an audio (e.g., a song), or a video (e.g., a movie). In some examples, searching a file or a folder is based on metadata associated with the folder or file. For example, the searching of a file or folder uses metadata such as a tag, a date, a time, an author, a title, a type of the file, a size, a page count, and/or a file location associated with the folder or file. In some examples, the file or folder can be stored internally or externally to the user device. For example, the file or folder can be stored on the hard disk of the user device or stored on a cloud server.


As illustrated in FIG. 8E, in accordance with the determination that the user intent is, for example, to display photos stored in a folder having a folder name “Colorado trip,” or display photos taken during the period of time that the user was travelling within Colorado, the digital assistant performs the task using the object managing process. For example, the digital assistant instantiates an object managing process represented by affordance 830 and causes the object managing process to search for photos from the user's Colorado trip. In some examples, the digital assistant also causes the object managing process to display a snippet or a window (not shown) providing text of the user's speech input 856.


With reference to FIG. 8F, in some embodiments, the digital assistant further provides a response based on a result of performing the task using the object managing process. As illustrated in FIG. 8F, as a result of searching the photos of the user's Colorado trip, the digital assistant displays a user interface 834 (e.g., a snippet or a window) providing the result of performing the task using the object managing process. For example, on user interface 834, a preview of the photos is displayed. In some examples, the digital assistant instantiates a process (e.g., the object managing process) to perform additional tasks on the photos, such as inserting the photos to a document or attaching the photos to email. As described in more detail below, the digital assistant can instantiate a process to perform the additional tasks in response to a user's additional speech input. As well, the digital assistant can perform multiple tasks in response to a single speech input, such as “send the photos from my Colorado trip to my Mom by email.” The digital assistant can also instantiate a process to perform such additional tasks in response to the user's input using an input device (e.g., a mouse input to select of one or more affordances or perform a drag-and-drop operation). In some embodiments, the digital assistant further provides a spoken output corresponding to the result. For example, the digital assistant provides a spoken output 876 including “Here are the photos from your Colorado trip.”


With reference to FIG. 9A, in some examples, user's speech input may not include one or more keywords indicating whether the user intent is to use the searching process or the object managing process. For example, the user provides a speech input 952 such as “What is the score of today's Warriors game?” Speech input 952 does not include keywords indicating “the searching process” or the “object managing process.” As a result, the keywords may not be available for the digital assistant to determine whether the user intent is to perform the task using the searching process or the object managing process.


In some embodiments, to determine whether the user intent is to perform the task using the searching process or the object managing process, the digital assistant determines whether the task is associated with searching based on the speech input. In some examples, a task that is associated with searching can be performed by either the searching process or the object managing process. For example, both the searching process and the object managing process can search a folder and a file. In some examples, the searching process can further search a variety of objects including online information sources (e.g., websites), communications (e.g., emails), contacts, calendars, or the like. In some examples, the object managing process may not be configured to search certain objects such as online information sources.


In accordance with a determination that the task is associated with searching, the digital assistant further determines whether performing the task requires the searching process. As described, if a task is associated with searching, either the searching process or the object managing process can be used to perform the task. However, the object managing process may not be configured to search certain objects. As a result, to determine whether the user intent is to use the searching process or the object managing process, the digital assistant further determines whether the task requires the searching process. For example, as illustrated in FIG. 9A, based on speech input 952, the digital assistant determines that the user intent is, for example, to obtain the score of today's Warriors game. According to the user intent, the digital assistant further determines that performing the task requires searching online information sources and therefore is associated with searching. The digital assistant further determines whether performing the task requires the searching process. As described, in some examples, the searching process is configured to search online information sources such as websites, while the object managing process may not be configured to search such online information sources. As a result, the digital assistant determines that searching online information sources (e.g., searching Warriors' website to obtain the score) requires the searching process.


With reference to FIG. 9B, in some embodiments, in accordance with a determination that performing the task requires the searching process, the digital assistant performs the task using the searching process. For example, in accordance with the determination that searching the score of today's Warriors game requires the searching process, the digital assistant instantiates a searching process represented by affordance 920, and causes the searching process to search score of today's Warriors game. In some examples, the digital assistant further causes the searching process to display a user interface 922 (e.g., a snippet or a window) providing text of user speech input 952 (e.g., “What is the score of today's Warriors game?”). User interface 922 includes one or more affordances 921 and 927. Similar to described above, affordance 921 (e.g., a close button) enables closing of user interface 922 and affordance 927 (e.g., a scrolling bar) enables scrolling within user interface 922 such that the user can view the entire content within user interface 922.


With reference to FIG. 9B, in some examples, based on the search results, the digital assistant further provides one or more responses. As illustrated in FIG. 9B, as a result of searching the score of today's Warriors game, the digital assistant displays a user interface 924 (e.g., a snippet or a window) providing the result of performing the task using the searching process. In some embodiments, user interface 924 is located within user interface 922 as a separate user interface. In some embodiments, user interfaces 924 and 922 are integrated together as a single user interface. In some examples, the digital assistant displays the user interface 924 providing the current search results (e.g., the Warriors game score) together with another user interface (e.g., user interface 824 shown on FIG. 8C) providing prior search results (e.g., the AAPL stock price). In some embodiments, the digital assistant only displays user interface 924 providing the current search results and does not display another user interface providing prior search results. As illustrated in FIG. 9B, the digital assistant only displays user interface 924 to provide the current search results (e.g., the Warriors game score). In some examples, affordance 927 (e.g., a scrolling bar) enables scrolling within user interface 922 such that the user can view the prior search results. Further, in some examples, prior search results dynamically update or refresh, e.g., such that stock prices, sports score, weather forecast, etc., update over time.


As illustrated in FIG. 9B, on user interface 924, the search result of the score of today's Warriors game is displayed (e.g., Warriors 104-89 Cavaliers). In some embodiments, user interface 924 further provides affordances 923 and 925. Affordance 923 enables closing of user interface 924. For example, if the digital assistant receives a user's selection of affordance 923, user interface 924 disappears or closes from the display of the user device. Affordance 925 enables moving or sharing of the search result displayed on user interface 924. For example, if the digital assistant receives the user's selection of affordance 925, it moves or shares user interface 924 (or the search result thereof) with a notification application. As shown in FIG. 9B, the digital assistant displays user interface 926 that is associated with the notification application to provide the search result of Warriors game score. As described, results of the performance the task are dynamically updated over time. For example, the Warriors game score can be dynamically updated over time while the game is ongoing and displayed on user interface 924 (e.g., the snippet or window) and/or on user interface 926 (e.g., the notification application user interface). In some embodiments, the digital assistant further provides a spoken output corresponding to the search result. For example, the digital assistant represented by affordance 940 or 941 provides a spoken output 972 such as “Warriors beats Cavaliers, 104-89.” In some examples, user interface 922 (e.g., a snippet or a window) provides text corresponding to spoken output 972.


As described above, in some embodiments, the digital assistant determines whether the task is associated with searching, and in accordance with such a determination, the digital assistant determines whether performing the task requires the searching process. With reference to FIG. 9C, in some embodiments, the digital assistant determines that performing the task does not require the searching process. For example, as illustrated in FIG. 9C, the digital assistant receives a speech input 954 such as “Show me all the files called Expenses.” Based on speech input 954 and context information, the digital assistant determines that user intent is to display all the files having the word “Expenses” (or a portion, a variation, a paraphrase thereof) contained in their file names, the metadata, the content of the files, or the like. According to the user intent, the digital assistant determines that the task to be performed includes searching all the files associated with the word “Expenses.” As a result, the digital assistant determines that performing the task is associated with searching. As described above, in some examples, the searching process and the object managing process can both perform searching of files. As a result, the digital assistant determines that performing the task of searching all the files associated with the word “Expenses” does not require the searching process.


With reference to FIG. 9D, in some examples, in accordance with a determination that performing the task does not require the searching process, the digital assistant determines, based on a pre-determined configuration, whether the task is to be performed using the searching process or the object managing process. For example, if both the searching process and the object managing process can perform the task, a pre-determined configuration may indicate that the task is to be performed using the searching process. The pre-determined configuration can be generated and updated using context information such as user preferences or user-specific data. For example, the digital assistant determines that historically, for a particular user, the searching process was selected more frequently than the object managing process for file searching. As a result, the digital assistant generates or updates the pre-determined configuration to indicate that the searching process is the default process for searching files. In some examples, the digital assistant generates or updates the pre-determined configuration to indicate that the object managing process is the default process.


As illustrated in FIG. 9D, based on a pre-determined configuration, the digital assistant determines that the task of searching all the files associated with the word “Expense” is to be performed using the searching process. As a result, the digital assistant performs the searching of all the files associated with the word “Expenses” using the searching process. For example, the digital assistant instantiates a searching process represented by affordance 920 displayed on user interface 910, and causes the searching process to search all files associated with the word “Expenses.” In some examples, the digital assistant further provides a spoken output 974, informing the user that the task is being performed. Spoken output 974 includes, for example, “OK, searching all files called ‘Expenses’.” In some examples, the digital assistant further causes the searching process to display a user interface 928 (e.g., a snippet or a window) providing text corresponding to speech input 954 and spoken output 974.


With reference to FIG. 9E, in some embodiments, the digital assistant further provides one or more responses based on a result of performing the task using the searching process. As illustrated in FIG. 9E, as a result of searching all files associated with the word “Expenses,” the digital assistant displays a user interface 947 (e.g., a snippet or a window) providing the search results. In some embodiments, user interface 947 is located within user interface 928 as a separate user interface. In some embodiments, user interfaces 947 and 928 are integrated together as a single user interface. On user interface 947, a list of files that are associated with the word “Expenses” are displayed. In some embodiments, the digital assistant further provides a spoken output corresponding to the search result. For example, the digital assistant represented by affordance 940 or 941 provides a spoken output 976 such as “Here are all the files called Expenses.” In some examples, the digital assistant further provides, on user interface 928, text corresponding to spoken output 976.


In some embodiments, the digital assistant provides one or more links associated with the result of performing the task using the searching process. A link enables instantiating a process (e.g., opening a file, invoking an object managing process) using the search result. As illustrated in FIG. 9E, on user interface 947, the list of files (e.g., Expenses File 1, Expenses File 2, Expenses File 3) represented by their file names can be associated with links. As an example, a link is displayed on the side of each file name. As another example, the file names is displayed in a particular color (e.g., blue) indicating that the file names are associated with links. In some examples, the file names associated with links are displayed in the same color as other items displayed on user interface 947.


As described, a link enables instantiating a process using the search result. Instantiating a process includes invoking the process if the process is not already running. If at least one instance of the process is running, instantiating a process includes executing an existing instance of the process or generating a new instance of the process. For example, instantiating an object managing process includes invoking the object managing process, using an existing object managing process, or generating a new instance of the object managing process. As illustrated in FIGS. 9E-9F, a link displayed on user interface 947 enables managing an object (e.g., a file) associated with the link. For example, user interface 947 receives a user selection of a link (e.g., a selection by a cursor 934) associated with a file (e.g., “Expenses file 3”). In response, the digital assistant instantiates an object managing process represented by affordance 930 to enable managing of the file. As shown in FIG. 9F, the digital assistant displays a user interface 936 (e.g., a snippet or a window) providing the folder containing the file associated with the link (e.g., “Expenses file 3”). Using user interface 936, the digital assistant instantiates the object managing process to perform one or more additional tasks (e.g., copying, editing, viewing, moving, compressing, or the like) with respect to the files.


With reference back to FIG. 9E, in some examples, a link displayed on user interface 947 enables direct viewing and/or editing of the object. For example, the digital assistant, via user interface 947, receives a selection of a link (e.g., a selection by a cursor 934) associated with a file (e.g., “Expenses file 3”). In response, the digital assistant instantiates a process (e.g., a document viewing/editing process) to view and/or edit the file. In some examples, the digital assistant instantiates the process to view and/or edit the file without instantiating an object managing process. For example, the digital assistant directly instantiates a Number process or an Excel process to view and/or edit of the Expense file 3.


With reference to FIGS. 9E and 9G, in some examples, the digital assistant instantiates a process (e.g., the searching process) to refine the search results. As illustrated in FIGS. 9E and 9G, the user may desire to refine the search result displayed on user interface 947. For example, the user may desire to select one or more files from the search results. In some examples, the digital assistant receives, from the user, a speech input 977 such as “Just the ones Kevin sent me that I tagged with draft.” Based on speech input 977 and context information, the digital assistant determines that the user intent is to display only the Expenses files that were sent from Kevin and that are associated with draft tags. Based on the user intent, the digital assistant instantiates a process (e.g., the searching process) to refine the search results. For example, as shown in FIG. 9G, based on the search result, the digital assistant determines that Expenses File 1 and Expense file 2 were sent from Kevin to the user and were tagged. As a result, the digital assistant continues to display these two files on user interface 947 and remove the Expense file 3 from user interface 947. In some examples, the digital assistant provides a spoken output 978 such as “Here are just the ones Kevin sent you that you tagged with draft.” The digital assistant may further provide text corresponding to spoken output 978 on user interface 928.


With reference to FIG. 9H, in some examples, the digital assistant instantiates a process (e.g., an object managing process) to perform an object managing task (e.g., coping, moving, sharing, etc.). For example, as shown in FIG. 9H, the digital assistant receives, from the user, a speech input 984 such as “Move the Expenses file 1 to Documents folder.” Based on speech input 984 and context information, the digital assistant determines that the user intent is to copy or move Expense file 1 from its current folder to Document folder. In accordance with the user intent, the digital assistant instantiates a process (e.g., the object managing process) to copy or move Expense file 1 from its current folder to Document folder. In some examples, the digital assistant provides a spoken output 982 such as “Ok, moving Expenses File 1 to your Documents folder.” In some examples, the digital assistant furthers provide text corresponding to spoken output 982 on user interface 928.


As described, in some examples, a user's speech input may not include keywords indicating whether the user intent is to perform the task using the search process or the object managing process. With reference to FIGS. 10A-10B, in some embodiments, the digital assistant determines that performing the task does not require the searching process. In accordance with the determination, the digital assistant provides a spoken output requesting the user to select the searching process or the object managing process. For example, as shown in FIG. 10A, the digital assistant receives, from the user, a speech input 1052 such as “Show me all the files called ‘Expenses.’” Based on speech input 1052 and context information, the digital assistant determines that the user intent is to display all the files associated with the word “Expense.” In accordance with the user intent, the digital assistant further determines that the task can be performed by either the searching process or the object managing process, and therefore does not require the search process. In some examples, the digital assistant provides a spoken output 1072 such as “Do you want to search using the searching process or the object managing process?” In some examples, the digital assistant receives, from the user, a speech input 1054 such as “Object managing process.” Speech input 1054 thus indicates that the user intent is to perform the task using the object managing process. According to the selection, for example, the digital assistant instantiates an object managing process represented by affordance 1030 to search all the files associated with the word “Expenses.” As shown in FIG. 10B, similar to those described above, as a result of the searching, the digital assistant displays a user interface 1032 (e.g., a snippet or a window) providing a folder containing the files associated with the word “Expenses”. Similar to those described above, using user interface 1032, the digital assistant instantiates the object managing process to perform additional one or more tasks (e.g., copying, editing, viewing, moving, compressing, or the like) with respect to the files.


With reference to FIGS. 11A-11B, in some embodiments, the digital assistant identifies context information and determines the user intent based on the context information and the user's speech input. As illustrated in FIG. 11A, the digital assistant represented by affordance 1140 or 1141 receives a speech input 1152 such as “Open the Keynote presentation I created last night.” In response to receiving speech input 1152, the digital assistant identifies context information such as the history of the user's interaction with the user device, the metadata associated with files that the user recently worked on, or the like. For example, the digital assistant identifies the metadata such as the date, the time, and the type of files the user worked on yesterday from 6p.m.-2a.m. Based on the identified context information and speech input 1152, the digital assistant determines that the user intent includes searching a Keynote presentation file associated with metadata indicating that the file was edited approximately 6p.m.-12a.m yesterday; and instantiating a process (e.g., a Keynote process) to open the presentation file.


In some examples, the context information includes application names or identifications (IDs). For example, a user's speech input provides “Open the Keynote presentation,” “find my Pages document,” or “find my HotNewApp documents.” The context information includes the application names (e.g., Keynote, Pages, HotNewApp) or application IDs. In some examples, the context information is dynamically updated or synchronized. For example, the context information is updated in real time after the user installs a new application named HotNewApp. In some examples, the digital assistant identifies the dynamically updated context information and determines the user intent. For example, the digital assistant identifies the application names Keynote, Pages, HotNewApp or their IDs and determines the user intent according to the application names/IDs and speech inputs.


In accordance with the user intent, the digital assistant further determines whether the user intent is to perform the task using the searching process or the object managing process. As described, the digital assistant makes such determination based on one or more keywords included in the speech input, based on whether the task requires the searching process, based on a pre-determined configuration, and/or based on the user's selection. As illustrated in FIG. 11A, speech input 1152 does not include keywords that indicate whether the user intent is to use the searching process or the object managing process. As a result, the digital assistant determines, for example, based on a pre-determined configuration that the user intent is to use the object managing process. In accordance with the determination, the digital assistant instantiate an object managing process to search a Keynote presentation file associated with metadata that indicates the file was edited approximately 6p.m.-12a.m yesterday. In some embodiments, the digital assistant further provides a spoken output 1172 such as “OK, looking for the Keynote presentation you created last night.”


In some embodiments, context information is used in performing the task. For example, application names and/or IDs can be used to form a query for searching the application and/or objects (e.g., files) associated with the application names/IDs. In some examples, a server (e.g., server 108) forms a query using the application names (e.g., Keynote, Pages, HotNewApp) and/or IDs and sends the query to the digital assistant of a user device. Based on the query, the digital assistant instantiates a searching process or an object managing process to search one or more applications and/or objects. In some examples, the digital assistant only searches the objects (e.g., files) that correspond to the application name/ID. For example, if a query includes an application name “Pages,” the digital assistant only searches Pages files and does not search other files (e.g., Word files) that can be opened by a Pages application. In some examples, the digital assistant searches all objects that is associated with the application name/ID in the query.


With references to FIGS. 11B-11C, in some embodiments, the digital assistant provides one or more responses in accordance with a confidence level associated with the results of performing the task. Inaccuracies may exist or arise during the determination of the user intent, the determination of whether the user intent is to perform the task using the searching process or the object managing process, and/or the performance of the task. In some examples, the digital assistant determines a confidence level representing the accuracy of determining the user intent based on the speech input and context information, the accuracy of determining whether the user intent is to perform the task using the searching process or the object managing process, the accuracy of performing the task using the searching process or the object managing process, or a combination thereof.


Continuing the above example illustrated in FIG. 11A, based on speech input 1152 such as “Open the Keynote presentation I created last night,” the digital assistant instantiates an object managing process to perform a search of a Keynote presentation file associated with metadata that indicates the file was edited approximately 6p.m.-12a.m yesterday. The search result may include a single file that fully matches the search criteria. That is, the single file is a presentation file that was edited approximately 6p.m.-12a.m yesterday. Accordingly, the digital assistant determines that the accuracy of the search is high and thus determines that the confidence level is high. As another example, the search result may include a plurality of files that partially match the search criteria. For instance, no file is a presentation file that was edited approximately 6p.m.-12a.m yesterday, or multiple files are presentation files that were edited approximately 6p.m.-12a.m yesterday. Accordingly, the digital assistant determines that the accuracy of the search is medium or low and thus determines that the confidence level is medium or low.


As illustrated in FIGS. 11B-11C, the digital assistant provides a response in accordance with the determination of the confidence level. In some examples, the digital assistant determines whether the confidence level is greater than or equal to a threshold confidence level. In accordance with a determination that the confidence level is greater than or equal to the threshold confidence level, the digital assistant provides a first response. In accordance with a determination that the confidence level is less than a threshold confidence level, the digital assistant provides a second response. In some examples, the second response is different from the first response. As shown in FIG. 11B, if the digital assistant determines that the confidence level is greater than or equal to a threshold confidence level, the digital assistant instantiates a process (e.g., a Keynote process represented by user interface 1142) to enable the viewing and editing of the file. In some examples, the digital assistant provides a spoken output such as “Here is the presentation you created last night,” and displays the text of the spoken output in a user interface 1143. As shown in FIG. 11C, if the digital assistant determines that the confidence level is less than a threshold confidence level, the digital assistant displays a user interface 1122 (e.g., a snippet or a window) providing a list of candidate files. Each of the candidate files may partially satisfy the search criteria. In some embodiments, the confidence level can be pre-determined and/or dynamically updated based on user preferences, historical accuracy rates, or the like. In some examples, the digital assistant further provides a spoken output 1174 such as “Here are all the presentations created last night,” and displays the text corresponding to spoken output 1174 on user interface 1122.


With reference to FIG. 11D, in some embodiments, the digital assistant instantiates a process (e.g., the Keynote presentation process) to perform additional tasks. Continuing with the above example, as shown in FIGS. 11B and 11D, the user may desire to display the presentation file in a full screen mode. The digital assistant receives, from the user, a speech input 1154 such as “Make it full screen.” Based on speech input 1154 and context information, the digital assistant determines that the user intent is to display the presentation file in a full screen mode. In accordance with the user intent, the digital assistant causes the Keynote presentation process to display the slides in a full-screen mode. In some examples, the digital assistant provides a spoken output 1176 such as “OK, showing your presentation in full screen.”


With reference to FIGS. 12A-12C, in some embodiments, the digital assistant determines, based on a single speech input or an utterance, that the user intent is to perform a plurality of tasks. In accordance with the user intent, the digital assistant further instantiates one or more processes to perform the plurality of tasks. For example, as shown in FIG. 12A, the digital assistant represented by affordance 1240 or 1241 receives a single speech input 1252 such as “Show me all the photos from my Colorado trip, and send them to my mom.” Based on speech input 1252 and context information, the digital assistant determines that the user intent is to perform a first task and a second task. Similar to those described above, the first task is to display photos stored in a folder having a folder name “Colorado trip,” or display photos taken during the period of time that the user is travelling within Colorado. With respect to the second task, the context information may indicate that a particular email address stored in the user's contacts is tagged as the user's mom. Accordingly, the second task is to send an email containing the photos associated with the Colorado trip to the particular email address.


In some examples, the digital assistant determines, with respect to each task, whether the user intent is to perform the task using the searching process or the object managing process. As an example, the digital assistant determines that the first task is associated with searching and the user intent is to perform the first task using the object managing process. As illustrated in FIG. 12B, in accordance with a determination the user intent is to perform the first task using the object managing process, the digital assistant instantiates the object managing process to search photos associated with the user's Colorado trip. In some examples, the digital assistant displays a user interface 1232 (e.g., a snippet or a window) providing a folder including the search result (e.g., photos 1, 2, and 3). As another example, the digital assistant determines that the first task is associated with searching and the user intent is to perform the first task using the searching process. As illustrated in FIG. 12C, in accordance with a determination the user intent is to perform the first task using the searching process, the digital assistant instantiates the searching process to search photos associated with the user's Colorado trip. In some examples, the digital assistant displays a user interface 1234 (e.g., a snippet or a window) providing photos and/or links associated with the search result (e.g., photos 1, 2, and 3).


As another example, the digital assistant determines that the second task (e.g., sending an email containing the photos associated with the Colorado trip to the particular email address) is not associated with searching or associated with managing an object. In accordance with the determination, the digital assistant determines whether the task can be performed using a process that is available to the user device. For example, the digital assistant determines that the second task can be performed using an email process at the user device. In accordance with the determination, the digital assistant instantiates the process to perform the second task. As illustrated in FIGS. 12B-12C, the digital assistant instantiates the email process and displays user interfaces 1242 and 1244 associated with the email process. The email process attaches the photos associated with the user's Colorado trip to email messages. As shown in FIGS. 12B-12C, in some embodiments, the digital assistant further provides spoken outputs 1272 and 1274 such as “Here are the photos from your Colorado trip. I am ready to send the photos to your mom, proceed?” In some examples, the digital assistant displays text corresponding to spoken output 1274 on user interface 1244. In response to spoken outputs 1272 and 1274, the user provides a speech input such as “OK.” Upon receiving the speech input from the user, the digital assistant causes the email process to send out the email messages.


Techniques for performing a plurality of tasks based on multiple commands contained within a single speech input or an utterance may be found, for example, in related applications: U.S. patent application Ser. No. 14/724,623, titled “MULTI-COMMAND SINGLE UTTERANCE INPUT METHOD,” filed May 28, 2015, which claims the benefit of priority of U.S. Provisional Patent Application No. 62/005,556, entitled “MULTI-COMMAND SINGLE UTTERANCE INPUT METHOD,” filed on May 30, 2014; and U.S. Provisional Patent Application No. 62/129,851, entitled “MULTI-COMMAND SINGLE UTTERANCE INPUT METHOD,” filed on Mar. 8, 2015. Each of these applications is hereby incorporated by reference in their entirety.


As illustrated in FIGS. 12C-12D, in some examples, the digital assistant causes a process to perform additional tasks based on the user's additional speech inputs. For example, in view of the search result displayed in user interface 1234, the user may desire to send some, but not all, of the photos. The user provides a speech input 1254 such as “Send only Photo 1 and Photo 2.” In some examples, the digital assistant receives speech input 1254 after the user selects affordance 1235 (e.g., a microphone icon displayed on user interface 1234). The digital assistant determines, based on speech input 1254 and context information, that the user intent is to send an email attaching only Photo 1 and Photo 2. In accordance with the user intent, the digital assistant causes the email process to remove Photo 3 from the email message. In some examples, the digital assistant provides a spoken output 1276, such as “OK, attaching Photo 1 and Photo 2 to your email,” and displays the text corresponding to spoken output 1276 on user interface 1234.


With reference to FIG. 13A, in some embodiments, in accordance with a determination that the task is not associated with searching, the digital assistant determines whether the task is associated with managing at least one object. As illustrated in FIG. 13A, for example, the digital assistant receives a speech input 1352 such as “Create a new folder on the desktop called Projects.” Based on speech input 1352 and context information, the digital assistant determines that the user intent is to generate a new folder at the desktop with a folder name “Projects.” The digital assistant further determines that the user intent is not associated with searching, and instead is associated with managing an object (e.g., a folder). Accordingly, the digital assistant determines that the user intent is to perform a task using the object managing process.


In some examples, in accordance with the determination that the user intent is to perform the task using the object managing process, the digital assistant performs the task using the object managing process. Performing the task using the object managing process can include, for example, creating at least one object (e.g., creating a folder or a file), storing at least one object (e.g., storing a folder, a file, or a communication), and compressing at least one object (e.g., compressing folders and files). Performing the task using the object managing process can further include, for example, copying or moving at least one object from a first physical or virtual storage to a second physical or virtual storage. For instance, the digital assistant instantiates an object managing process to cut and paste a file from the user device to a flash drive or a cloud drive.


Performing the task using the object managing process can further include, for example, deleting at least one object stored in a physical or virtual storage (e.g., deleting a folder or a file) and/or recovering at least one object stored at a physical or virtual storage (e.g., recovering a deleted folder or a deleted file). Performing the task using the object managing process can further include, for example, marking at least one object. In some examples, marking of an object can be visible or invisible. For example, the digital assistant can cause the object managing process to generate a “like” sign for a social media post, to tag an email, to mark a file, or the like. The marking may be visible by displaying, for example, a flag, a sign, or the like. The marking may also be performed with respect to the metadata of the object such that a storage (e.g., a memory) content of the metadata is varied. The metadata may or may not be visible.


Performing the task using the object managing process can further include, for example, backing up at least one object according to a predetermined time period for backing up or upon the user's request. For example, the digital assistant can cause the object managing process to instantiate a backup program (e.g., time machine program) to backup folders and files. The backup can be performed automatically according to a pre-determined schedule (e.g., once a day, a week, a month, or the like) or according to a user request.


Performing the task using the object managing process can further include, for example, sharing at least one object among one or more electronic devices communicatively connected to the user device. For example, the digital assistant can cause the object managing process to share a photo stored on the user device with another electronic device (e.g., the user's smartphone or tablet).


As illustrated in FIG. 13B, in accordance with the determination that the user intent is to perform the task using the object managing process, the digital assistant performs the task using the object managing process. For example, the digital assistant instantiates an object managing process to generate a folder named “Projects” on the desktop of user interface 1310. In some examples, the digital assistant can cause the object managing process to further open the folder either automatically or in response to an additional user input. For example, the digital assistant provides a spoken output 1372 such as “OK, I've created a folder on the desktop called Projects, would you like to open it?” The user provides a speech input 1374 such as “Yes.” In response to the user's speech input 1374, the digital assistant causes the object managing process to open the Projects folder and display a user interface 1332 corresponding to the Projects folder.


With reference to FIG. 13C, in some embodiments, the digital assistant provides one or more affordances that enable the user to manipulate the result of performing the task using the searching process or the object managing process. The one or more affordances include, for example, an edit button, a cancel button, a redo button, an undo button, or the like. For example, as shown in FIG. 13C, after generating the folder named “Projects” on the desktop, the digital assistant provides a user interface 1334, which displays an edit button 1336A, an undo button 1336B, and a redo button 1336C. In some examples, the edit button 1336A enables the user to edit one or more aspects of the object (e.g., edit the name of the Projects folder); the undo button 1336B enables the user to reverse the last task performed by the object managing process (e.g., delete the Projects folder); and the redo button 1336C enables the user to repeat the last task performed by the object managing process (e.g., creating another folder using the object managing process). It is appreciated that the digital assistant can provide any desired affordances to enable the user to perform any manipulation of the result of performing a task using the searching process or the object managing process.


As described, the digital assistant can determine whether the user intent is to perform a task using a searching process or an object managing process. In some examples, the digital assistant determines that the user intent is not associated with the searching process or the object managing process. For example, the user provides a speech input such as “start dictation.” The digital assistant determines that the task of dictation is not associated with searching. In some examples, in accordance with a determination that the task is not associated with searching, the digital assistant further determines whether the task is associated with managing at least one object. For example, the digital assistant determines that the task of dictation is also not associated with managing an object, such as copying, moving, or deleting a file, a folder, or an email. In some examples, in accordance with a determination that the task is not associated with managing an object, the digital assistant determines whether the task can be performed using a process available to the user device. For example, the digital assistant determines that the task of dictation can be performed using a dictation process that is available to the user device. In some examples, the digital assistant initiates a dialog with the user with respect to performing the task using a process available to the user device. For example, the digital assistant provides a spoken output such as “OK, starting dictation.” or “Would you like to dictate in this presentation you are working now?” After providing the spoken output, the digital assistant receives a response from the user, for example, confirming that the user intent is to dictate in the presentation the user is currently working on.


5. Exemplary Functions of a Digital Assistant—Continuity



FIGS. 14A-14D, 15A-15D, 16A-16C, and 17A-17E illustrate functionalities of performing a task at a user device or a first electronic device using remotely located content by a digital assistant. In some examples, the digital assistant system (e.g., digital assistant system 700) is implemented by a user device (e.g., devices 1400, 1500, 1600, and 1700) according to various examples. In some examples, the user device, a server (e.g., server 108), or a combination thereof, may implement a digital assistant system (e.g., digital assistant system 700). The user device can be implemented using, for example, device 104, 200, or 400. In some examples, the user device can be a laptop computer, a desktop computer, or a tablet computer. The user device operates in a multi-tasking environment, such as a desktop environment.


With references to FIGS. 14A-14D, 15A-15D, 16A-16C, and 17A-17E, in some examples, a user device (e.g., devices 1400, 1500, 1600, and 1700) provides various user interfaces (e.g., user interfaces 1410, 1510, 1610, and 1710). Similar to those described above, the user device displays the various user interfaces on a display, and the various user interfaces enable the user to instantiate one or more processes (e.g., a movie process, a photo process, a web-browsing process).


As shown in FIGS. 14A-14D, 15A-15D, 16A-16C, and 17A-17E, similar to those described above, the user device (e.g., devices 1400, 1500, 1600, and 1700) displays, on a user interface (e.g., user interfaces 1410, 1510, 1610, and 1710) an affordance (e.g., affordance 1440, 1540, 1640, and 1740) to instantiate a digital assistant service. Similar to those described above, in some examples, the digital assistant is instantiated in response to receiving a pre-determined phrase. In some examples, the digital assistant is instantiated in response to receiving a selection of the affordance.


With reference to FIGS. 14A-14D, 15A-15D, 16A-16C, and 17A-17E, in some embodiments, a digital assistant receives one or more speech inputs, such as speech inputs 1452, 1454, 1456, 1458, 1552, 1554, 1556, 1652, 1654, 1656, 1752, and 1756 from a user. The user may provide various speech inputs for the purpose of, for example, performing a task at the user device (e.g., devices 1400, 1500, 1600, and 1700) or at a first electronic device (e.g., electronic devices 1420, 1520, 1530, 1522, 1532, 1620, 1622, 1630, 1720, and 1730) using remotely located content. Similar to those described above, in some examples, the digital assistant can receive speech inputs directly from the user at the user device or indirectly through another electronic device that is communicatively connected to the user device.


With reference to FIGS. 14A-14D, 15A-15D, 16A-16C, and 17A-17E, in some embodiments, the digital assistant identifies context information associated with the user device. The context information includes, for example, user-specific data, sensor data, and user device configuration data. In some examples, the user-specific data includes log information indicating user preferences, the history of user's interaction with the user device (e.g., devices 1400, 1500, 1600, and 1700), and/or electronic devices communicative connected to the user device, or the like. For example, user-specific data indicates that the user recently took a self-portrait photo using an electronic device 1420 (e.g., a smartphone); that the user recently accessed a podcast, webcast, movie, song, audio book, or the like. In some examples, the sensor data includes various data collected by a sensor associated with the user device or other electronic devices. For example, the sensor data includes GPS location data indicating the physical location of the user device or electronic devices communicatively connected to the user device at any time point or during any time period. For example, the sensor data indicates that a photo stored in electronic device 1420 was taken at Hawaii. In some examples, the user device configuration data includes the current or historical device configurations. For example, the user device configuration data indicates that the user device is currently communicatively connected to some electronic devices but disconnected from other electronic devices. The electronic devices includes, for example, a smartphone, a set-top box, a tablet, or the like. As described in more detail below, the context information can be used in determining a user intent and/or in performing one or more tasks.


With reference to FIGS. 14A-14D, 15A-15D, 16A-16C, and 17A-17E, similar to those described above, in response to receiving a speech input, the digital assistant determines a user intent based on the speech input. The digital assistant determines the user intent based on a result of natural language processing. For example, the digital assistant identifies an actionable intent based on the user input, and generates a structured query to represent the identified actionable intent. The structured query includes one or more parameters associated with the actionable intent. The one or more parameters can be used to facilitate the performance of a task based on the actionable intent. For example, based on a speech input such as “show the selfie I just took,” the digital assistant determines that the actionable intent is to display a photo, and the parameters include a self-portrait that the user recently took during the past few days. In some embodiments, the digital assistant further determines the user intent based on the speech input and context information. For example, the context information indicates that the user device is communicatively connected to the user's phone using a Bluetooth connection and indicates that a self-portrait photo was added to the user's phone two days ago. As a result, the digital assistant determines that the user intent is to display a photo that is a self-portrait that was added to the user's phone two days ago. Determining the user intent based on speech input and context information is described in more detail below in various examples.


In some embodiments, in accordance with user intent, the digital assistant further determines whether the task is to be performed at the user device or at a first electronic device communicatively connected to the user device. Various examples of the determination are provided below in more detail with respect to FIGS. 14A-14D, 15A-15D, 16A-16C, and 17A-17E.


With reference to FIG. 14A, in some examples, user device 1400 receives a speech input 1452 from a user to invoke the digital assistant. As shown in FIG. 14A, in some examples, the digital assistant is represented by affordances 1440 or 1441 displayed on user interface 1410. Speech input 1452 includes, for example, “Hey, Assistant.” In response to speech input 1452, user device 1400 invokes the digital assistant such that the digital assistant actively monitors subsequent speech inputs. In some examples, the digital assistant provides a spoken output 1472 indicating that it is invoked. For example, spoken output 1472 includes “Go ahead, I am listening.” As shown in FIG. 14A, in some examples, user device 1400 is communicatively connected to one or more electronic devices such as electronic device 1420. Electronic device 1420 can communicate with user device 1400 using wired or wireless networks. For example, electronic device 1420 communicates with user device 1400 using Bluetooth connections such that voice and data (e.g., audio and video files) can be exchanged between the two devices.


With reference to FIG. 14B, in some examples, the digital assistant receives a speech input 1454 such as “Show me the selfie I just took using my phone on this device.” Based on speech input 1454 and/or context information, the digital assistant determines the user intent. For example, as shown in FIG. 14B, context information indicates that the user device 1400 is communicatively connected to electronic device 1420 using wired or wireless networks (e.g., a Bluetooth connection, a Wi-Fi connection, or the like). Context information also indicates that the user recently took a self-portrait, which is stored in electronic device 1420 with a name “selfie0001.” As a result, the digital assistant determines that the user intent is to display the photo named selfie0001 stored in electronic device 1420. Alternatively, the photo may have been tagged with photo recognition software as containing the user's face and be identified accordingly.


As described, in accordance with the user intent, the digital assistant further determines whether the task is to be performed at the user device or at a first electronic device communicatively connected to the user device. In some embodiments, determining whether the task is to be performed at the user device or at the first electronic device is based on one or more keywords included in the speech input. For example, the digital assistant determines that speech input 1454 includes keywords or a phrase such as “on this device,” indicating the task is to be performed on user device 1400. As a result, the digital assistant determines that displaying the photo named selfie0001 stored in electronic device 1420 is to be performed at user device 1400. User device 1400 and electronic device 1420 are different devices. For example, user device 1400 can be a laptop computer, and electronic device 1420 can be a phone.


In some embodiments, the digital assistant further determines whether the content associated with the performance of the task is located remotely. Content is located remotely if at or near the time the digital assistant determines which device is to perform the task, at least a portion of the content for performing the task is not stored in the device that is determined to perform the task. For example, as shown in FIG. 14B, at or near the time the digital assistant of user device 1400 determines that the user intent is to display the photo named selfie0001 at user device 1400, the photo named selfie0001 is not stored at user device 1400 and instead is stored at electronic device 1420 (e.g., a smartphone). Accordingly, the digital assistant determines that the photo is located remotely to user device 1400.


As illustrated in FIG. 14B, in some embodiments, in accordance with a determination that the task is to be performed at the user device and content for performing the task is located remotely, the digital assistant of the user device receives the content for performing the task. In some examples, the digital assistant of the user device 1400 receives at least a portion of the content stored in the electronic device 1420. For example, to display the photo named selfie0001, the digital assistant of user device 1400 sends a request to electronic device 1420 to obtain the photo named selfie0001. Electronic device 1420 receives the request and, in response, transmits the photo named selfie0001 to user device 1400. The digital assistant of user device 1400 then receives the photo named selfie0001.


As illustrated in FIG. 14B, in some embodiments, after receiving the remotely located content, the digital assistant provides a response at the user device. In some examples, providing a response includes performing the task using the received content. For example, the digital assistant of user device 1400 displays a user interface 1442 (e.g., a snippet or a window) providing a view 1443 of the photo named selfie0001. View 1443 can be a preview (e.g., a thumbnail), an icon, or a full view of the photo named selfie0001.


In some examples, providing a response includes providing a link that is associated with the task to be performed at the user device. A link enables instantiating of a process. As described, instantiating a process includes invoking the process if the process is not already running. If at least one instance of the process is running, instantiating a process includes executing an existing instance of the process or generating a new instance of the process. As shown in FIG. 14B, user interface 1442 may provide a link 1444 associated with view 1443 of the photo named selfie0001. Link 1444 enables, for example, instantiating a photo process to view a full representation of the photo or edit the photo. As an example, link 1444 is displayed on the side of view 1443. As another example, view 1443 can itself include or incorporate link 1444 such that a selection of view 1443 instantiates a photo process.


In some embodiments, providing a response includes providing one or more affordances that enable the user to further manipulate the results of the performance of the task. As shown in FIG. 14B, in some examples, the digital assistant provides affordances 1445 and 1446 on user interface 1442 (e.g., a snippet or a window). Affordance 1445 can include a button for adding a photo to an album, and affordance 1446 can include a button for canceling view 1443 of the photo. The user may select one or both of affordances 1445 and 1446. In response to the selection of affordance 1445, for example, a photo process adds the photo associated with view 1443 to an album. In response to the selection of affordance 1446, for example, a photo process removes view 1443 from user interface 1442.


In some embodiments, providing a response includes providing a spoken output according to the task to be performed at the user device. As illustrated in FIG. 14B, the digital assistant represented by affordances 1440 or 1441 provides a spoken output 1474 such as “Here is the last selfie from your phone.”


With reference to FIG. 14C, in some examples, based on a single speech input/utterance and context information, the digital assistant determines that the user intent is to perform a plurality of tasks. As shown in FIG. 14C, the digital assistant receives a speech input 1456 such as “Show me the selfie I just took using my phone on this device and set it as my wallpaper.” Based on speech input 1456 and context information, the digital assistant determines that the user intent is to perform a first task of displaying the photo named selfie0001 stored at electronic device 1420 and performs a second task of setting the photo named selfie0001 as the wallpaper. Thus, based on a single speech input 1456, the digital assistant determines that the user intent is to perform multiple tasks.


In some embodiments, the digital assistant determines whether the plurality of tasks is to be performed at the user device or at an electronic device communicatively connected to the user device. For example, using the keywords “this device” included in speech input 1456, the digital assistant determines that the plurality of tasks is to be performed at user device 1400. Similar to those described above, the digital assistant further determines whether the content for performing at least one task is located remotely. For example, the digital assistant determines that the content for performing at least the first task (e.g., displaying the photo named selfie0001) is located remotely. In some embodiments, in accordance with a determination that the plurality of tasks is to be performed at the user device and content for performing at least one task is located remotely, the digital assistant requests the content from another electronic device (e.g., electronic device 1420), receives the content for performing the tasks, and provides a response at the user device.


In some embodiments, providing a response includes performing the plurality of tasks. For example, as illustrated in FIG. 14C, providing a response includes performing the first task of displaying a view 1449 of the photo named selfie0001, and performing the second task of setting the photo named selfie0001 as the wallpaper. In some examples, the digital assistant automatically configures the wallpaper to be the photo named selfie0001 using a desktop settings configuration process. In some examples, the digital assistant provides a link to desktop settings 1450, enabling the user to manually configure the wallpaper using the photo named selfie0001. For example, the user may select the link to desktop settings 1450 by using an input device such as a mouse, a stylus, or a finger. Upon receiving the selection of the link to desktop setting 1450, the digital assistant initiates the desktop setting configuration process that enables the user to select the photo named selfie0001 and set it as the wallpaper of user device 1400.


As illustrated in FIG. 14C, in some examples, the digital assistant initiates a dialog with the user and facilitates the configuration of the wallpaper in response to receiving a speech input from the user. For example, the digital assistant provides a spoken output 1476 such as “Here is the last selfie from your phone. Set is as wallpaper?” The user provides a speech input such as “OK.” Upon receiving the speech input, the digital assistant instantiates the desktop settings configuration process to configure the wallpaper as the photo named selfie0001.


As described, in some examples, the digital assistant determines the user intent based on the speech input and context information. With reference to FIG. 14D, in some examples, the speech input may not include information sufficient to determine the user intent. For example, the speech input may not indicate the location of the content for performing the task. As shown in FIG. 14D, the digital assistant receives a speech input 1458 such as “Show me the selfie I just took.” Speech input 1458 does not include one or more keywords indicating which photo is to be displayed or the location of the selfie to be displayed. As a result, the user intent may not be determined based solely on speech input 1458. In some examples, the digital assistant determines the user intent based on speech input 1458 and context information. For example, based on context information, the digital assistant determines that user device 1400 is communicatively connected to electronic device 1420. In some examples, the digital assistant instantiates a searching process to search for photos that the user recently took at user device 1400 and electronic device 1420. Based on the search result, the digital assistant determines that a photo named selfie0001 is stored in electronic device 1420. Accordingly, the digital assistant determines that the user intent is to display the photo named selfie0001 located at electronic device 1420. In some examples, if the user intent cannot be determined based on the speech input and context information, the digital assistant initiates a dialog with the user to further clarify or disambiguate the user intent.


As illustrated in FIG. 14D, in some examples, the speech input may not include one or more keywords indicating whether a task is to be performed at the user device or at an electronic device communicatively connected to the user device. For example, speech input 1458 does not indicate whether the task of displaying the selfie is to be performed at user device 1400 or at electronic device 1420. In some examples, the digital assistant determines whether a task is to be performed at the user device or at an electronic device based on context information. As an example, the context information indicates that the digital assistant receives speech input 1458 at user device 1400, not at electronic device 1420. As a result, the digital assistant determines that the task of displaying the selfie is to be performed at user device 1400. As another example, context information indicates that a photo is to be displayed on electronic device 1420 according to user preferences. As a result, the digital assistant determines that the task of displaying the selfie is to be performed at electronic device 1420. It is appreciated that the digital assistant can determine whether a task is to be performed at the user device or at an electronic device based on any context information.


With reference to FIG. 15A, in some embodiments, a digital assistant determines that the task is to be performed at an electronic device (e.g., electronic device 1520 and/or 1530) communicatively connected to the user device (e.g., user device 1500) and determine that the content is located remotely to the electronic device. As shown in FIG. 15A, in some examples, the digital assistant receives a speech input 1552 such as “Play this movie on my TV.” As described, the digital assistant can determine the user intent based on speech input 1552 and context information. For example, context information indicates that user interface 1542 is displaying a movie named ABC.mov. As a result, the digital assistant determines that the user intent is to play the movie named ABC.mov.


In accordance with the user intent, the digital assistant furthers determine whether the task is to be performed at the user device or at a first electronic device communicatively connected to the user device. In some embodiments, determining whether the task is to be performed at the user device or at the first electronic device is based on one or more keywords included in the speech input. For example, speech input 1552 includes the words or phrase “on my TV.” In some examples, context information indicates that user device 1500 is connected to a set-top box 1520 and/or a TV 1530 using, for example, a wired connection, a Bluetooth connection, or a Wi-Fi connection. As a result, the digital assistant determines that the task of playing the movie named ABC.mov is to be performed on set-top box 1520 and/or TV 1530.


In some embodiments, the digital assistant further determines whether the content associated with the performance of the task is located remotely. As described, content is located remotely if at or near the time the digital assistant determines which device is to perform the task, at least a portion of the content for performing the task is not stored in the device that is determined to perform the task. For example, as shown in FIG. 15A, at or near the time the digital assistant of user device 1500 determines that movie ABC.mov is to be played at set-top box 1520 and/or TV 1530, at least a portion of the movie ABC.mov is stored at user device 1500 (e.g., a laptop computer) and/or a server (not shown) and is not stored at set-top box 1520 and/or TV 1530. Accordingly, the digital assistant determines that the movie ABC.mov is located remotely to set-top box 1520 and/or TV 1530.


With reference to FIG. 15B, in accordance with a determination that the task is to be performed at the first electronic device (e.g., set-top box 1520 and/or TV 1530) and the content for performing the task is located remotely to the first electronic device, the digital assistant of the user device provides the content to the first electronic device to perform the task. For example, to play the movie ABC.mov on set-top box 1520 and/or TV 1530, the digital assistant of user device 1500 transmits at least a portion of the movie ABC.mov to set-top box 1520 and/or TV 1530.


In some examples, instead of providing the content from the user device, the digital assistant of the user device causes at least a portion of the content to be provided from another electronic device (e.g., a server) to the first electronic device to perform the task. For example, the movie ABC.mov is stored in a server (not shown) and not at user device 1500. As a result, the digital assistant of user device 1500 causes at least a portion of the movie named ABC.mov to be transmitted from the server to set-top box 1520 and/or TV 1530. In some examples, the content for performing the task is provided to set-top box 1520, which then transmits the content to TV 1530. In some examples, the content for performing the task is provided to TV 1530 directly.


As illustrated in FIG. 15B, in some examples, after the content is provided to the first electronic device (e.g., set-top box 1520 and/or TV 1530), the digital assistant of user device 1500 provides a response at user device 1500. In some examples, providing the response includes causing the task to be performed at set-top box 1520 and/or TV 1530 using the content. For example, the digital assistant of user device 1500 sends a request to set-top box 1520 and/or TV 1530 to initiate a multimedia process to play the movie ABC.mov. In response to the request, set-top box 1520 and/or TV 1530 initiates the multimedia process to play the movie ABC.mov.


In some examples, the task to be performed at the first electronic device (e.g., set-top box 1520 and/or TV 1530) is a continuation of a task performed remotely to the first electronic device. For example, as illustrated in FIGS. 15A-15B, the digital assistant of user device 1500 has caused a multimedia process of user device 1500 to play a portion of the movie ABC.mov at user device 1500. In accordance with the determination that the user intent is to play the movie ABC.mov at the first electronic device (e.g., set-top box 1520 and/or TV 1530), the digital assistant of user device 1500 causes the first electronic device to continue playing the rest of the movie ABC.mov rather than start playing from the beginning. As a result, the digital assistant of user device 1500 enables the user to continuously watch the movie.


As illustrated in FIG. 15B, in some embodiments, providing a response includes providing one or more affordances that enable the user to further manipulate the results of the performance of the task. As shown in FIG. 15B, in some examples, the digital assistant provides affordances 1547 and 1548 on a user interface 1544 (e.g., a snippet or a window). Affordance 1547 can be a button for cancelling the playing of movie ABC.mov on the first electronic device (e.g., set-top box 1520 and/or TV 1530). Affordance 1548 can be a button to pause or resume the playing of movie ABC.mov that is playing on the first electronic device. The user may select affordance 1547 or 1548 using an input device such as a mouse, a stylus, or a finger. Upon receiving a selection of affordance 1547, for example, the digital assistant causes the playing of movie ABC.mov on the first electronic device to stop. In some examples, after the playing on the first electronic device stops, the digital assistant also causes the playing of movie ABC.mov on user device 1500 to resume. Upon receiving a selection of affordance 1548, for example, the digital assistant causes the playing of movie ABC.mov on the first electronic device to pause or resume.


In some embodiments, providing a response includes providing a spoken output according to the task to be performed at the first electronic device. As illustrated in FIG. 15B, the digital assistant represented by affordance 1540 or 1541 provides a spoken output 1572 such as “Playing your movie on TV.”


As described, in accordance with a determination that the task is to be performed at a first electronic device and the content for performing the task is located remotely to the first electronic device, the digital assistant provides the content for performing the task to the first electronic device. With reference to FIG. 15C, the content for performing the task can include, for example, a document (e.g., document 1560) or location information. For instance, the digital assistant of user device 1500 receives a speech input 1556 such as “Open this pdf on my tablet.” The digital assistant determines that the user intent is to perform a task of displaying document 1560 and determines that the task is to be performed at a tablet 1532 that is communicatively connected to user device 1500. As a result, the digital assistant provides document 1560 to tablet 1532 to be displayed. As another example, the digital assistant of user device 1500 receives a speech input 1554 such as “Send this location to my phone.” The digital assistant determines that the user intent is to perform a task of navigation using the location information and determines that the task is to be performed at phone 1522 (e.g., a smartphone) that is communicatively connected to user device 1500. As a result, the digital assistant provides location information (e.g., 1234 Main St.) to phone 1522 to perform the task of navigation.


As described, in some examples, after providing the content for performing the task to the first electronic device, the digital assistant provides a response at the user device. In some embodiments, providing the response includes causing the task to be performed at the first electronic device. For example, as shown in FIG. 15D, the digital assistant of user device 1500 transmits a request to phone 1522 to perform the task of navigating to the location 1234 Main St. The digital assistant of user device 1500 further transmits a request to tablet 1532 to perform the task of displaying document 1560. In some examples, providing the response at the user device includes providing a spoken output according to the task to be performed at the first electronic device. As illustrated in FIG. 15D, the digital assistant provides a spoken output 1574 such as “Showing the pdf on your tablet” and a spoken output 1576 such as “navigating to 1234 Main St on your phone.”


As described, in some examples, the speech input may not include one or more keywords indicating whether a task is to be performed at the user device or at a first electronic device communicatively connected to the user device. With reference to FIG. 16A, for example, the digital assistant receives a speech input 1652 such as “Play this movie.” Speech input 1652 does not indicate whether the task of playing the movie is to be performed at user device 1600 or at a first electronic device (e.g., set-top box 1620 and/or TV 1630, phone 1622, or tablet 1632).


In some embodiments, to determine whether the task is to be performed at the user device or at a first electronic device, the digital assistant of the user device determines whether performing the task at the user device satisfies performance criteria. Performance criteria facilitate evaluating the performance of the task. For example, as illustrated in FIG. 16A, the digital assistant determines that the user intent is to perform the tasking of playing the movie ABC.mov. Performance criteria for playing a movie include, for example, the quality criteria of playing a movie (e.g., 480p, 720p, 1080p), the smoothness criteria of playing the movie (e.g., no delay or waiting), the screen size criteria (e.g., a minimum screen size of 48 inches), the sound effect criteria (e.g., stereo sounds, number of speakers), or the like. The performance criteria can be pre-configured and/or dynamically updated. In some examples, the performance criteria are determined based on context information such as user-specific data (e.g., user preferences), device configuration data (e.g., screen resolution and size of the electronic devices), or the like.


In some examples, the digital assistant of user device 1600 determines that performing the task at the user device satisfies the performance criteria. For example, as illustrated in FIG. 16A, user device 1600 may have a screen resolution, a screen size, and sound effect that satisfy the performance criteria of playing the movie ABC.mov, which may be a low-resolution online video. In accordance with a determination that performing the task at user device 1600 satisfies the performance criteria, the digital assistant determines that the task is to be performed at user device 1600.


In some examples, the digital assistant of user device 1600 determines that performing the task at the user device does not satisfy the performance criteria. For example, user device 1600 may not have the screen size, the resolution, and/or the sound effect to satisfy the performance criteria of playing the movie ABC.mov, which may be a high-resolution Blu-ray video. In some examples, in accordance with a determination that performing the task at the user device does not satisfy the performance criteria, the digital assistant of user device 1600 determines whether performing the task at the first electronic device satisfies the performance criteria. As illustrated in FIG. 16B, the digital assistant of user device 1600 determines that performing the task of playing the movie ABC.mov at set-top box 1620 and/or TV 1630 satisfies the performance criteria. For example, set-top box 1620 and/or TV 1630 may have a screen size of 52 inches, may have a 1080p resolution, and may have eight speakers connected. As a result, the digital assistant determines that the task is to be performed at set-top box 1620 and/or TV 1630.


In some examples, the digital assistant of user device 1600 determines that performing the task at the first electronic device does not satisfy the performance criteria. In accordance with the determination, the digital assistant determines whether performing the task at the second electronic device satisfies the performance criteria. For example, as illustrated in FIG. 16B, TV 1630 may have a screen resolution (e.g., 720p) that does not satisfy the performance criteria (e.g., 1080p). As a result, the digital assistant determines whether any one of phone 1622 (e.g., a smartphone) or tablet 1632 satisfies the performance criteria.


In some examples, the digital assistant determines which device provides the optimum performance of the task. For example, as illustrated in FIG. 16B, the digital assistant evaluates or estimates the performance of the task of playing movie ABC.mov on each of user device 1600, set-top box 1620 and TV 1630, phone 1622, and tablet 1632. Based on the evaluation or estimation, the digital assistant determines whether performing the task at one device (e.g., user device 1600) is better than at another device (e.g., phone 1622) and determines a device for optimum performance.


As described, in some examples, in accordance with the determination of a device for performing the task, the digital assistant provides a response at user device 1600. In some embodiments, providing a response includes providing a spoken output according to the task to be performed at the device. As illustrated in FIG. 16B, the digital assistant represented by affordances 1640 or 1641 provides a spoken output 1672 such as “I will play this movie on your TV, proceed?” In some examples, the digital assistant receives a speech input 1654 such as “OK” from the user. In response, the digital assistant causes the movie ABC.mov to be played at, for example, set-top box 1620 and TV 1630 and provides a spoken output 1674 such as “Playing your movie on your TV.”


In some examples, providing a response includes providing one or more affordances that enable the user to select another electronic device for performance of the task. As illustrated in FIG. 16B, for example, the digital assistant provides affordances 1655A-B (e.g., a cancel button and a tablet button). Affordance 1655A enables the user to cancel playing the movie ABC.mov at set-top box 1620 and TV 1630. Affordance 1655B enables the user to select tablet 1632 to continue playing the movie ABC.mov.


With reference to FIG. 16C, in some embodiments, to determine a device for performing a task, the digital assistant of user device 1600 initiates a dialog with the user. For example, the digital assistant provides a spoken output 1676 such as “Should I play your movie on the TV or on the tablet?” The user provides a speech input 1656 such as “On my tablet.” Upon receiving speech input 1656, the digital assistant determines that the task of playing the movie is to be performed at tablet 1632, which is communicatively connected to user device 1600. In some examples, the digital assistant further provides a spoken output 1678 such as “Playing your movie on your tablet.”


With reference to FIG. 17A, in some embodiments, a digital assistant of a user device 1700 continues to perform a task that was partially performed remotely at a first electronic device. In some embodiments, the digital assistant of a user device continues to perform the task using content received from a third electronic device. As illustrated in FIG. 17A, in some examples, phone 1720 may have been performing a task of flight booking using content from a third electronic device such as a server 1730. For example, the user may have been using phone 1720 to book flights from Kayak.com. As a result, phone 1720 receives content transmitted from server 1730 that is associated with Kayak.com. In some examples, the user may be interrupted while booking his or her flight on phone 1720 and may desire to continue the flight booking using user device 1700. In some examples, the user may desire to continue the flight booking simply because using user device 1700 is more convenient. Accordingly, the user may provide a speech input 1752 such as “Continue the flight booking on Kayak from my phone.”


With reference to FIG. 17B, upon receiving speech input 1752, the digital assistant determines the user intent is to perform a task of flight booking. In some examples, the digital assistant further determines that the task is to be performed at user device 1700 based on context information. For example, the digital assistant determines that speech input 1752 is received at user device 1700 and therefore determines that the task is to be performed at user device 1700. In some examples, the digital assistant further uses context information such as user preferences (e.g., user device 1700 is used frequently in the past for flight booking) to determine that the task is to be performed at user device 1700.


As shown in FIG. 17B, in accordance with the determination that the task is to be performed at the user device 1700, and the content for performing the task is located remotely, the digital assistant receives the content for performing the task. In some examples, the digital assistant receives the at least a portion of the content from phone 1720 (e.g., a smartphone) and/or at least a portion of the content from server 1730. For example, the digital assistant receives data representing the status of flight booking from phone 1720 such that user device 1700 can continue the flight booking. In some examples, the data representing the status of flight booking is stored at server 1730, such as a server associated with Kayak.com. The digital assistant thus receives data from server 1730 for continuing the flight booking.


As illustrated in FIG. 17B, after receiving the content from phone 1720 and/or server 1730, the digital assistant provides a response at user device 1700. In some examples, providing the response includes continuing to perform the task of flight booking that was partially performed remotely at phone 1720. For example, the digital assistant displays a user interface 1742 enabling the user to continue booking the flight on Kayak.com. In some examples, providing the response includes providing a link associated with the task to be performed at user device 1700. For example, the digital assistant displays a user interface 1742 (e.g., a snippet or a window) providing the current status of flight booking (e.g., showing available flights). User interface 1742 also provides a link 1744 (e.g., a link to a web browser) for continuing performing the task of flight booking. In some embodiments, the digital assistant also provides a spoken output 1772 such as “Here is the booking on Kayak. Continue in your web browser?”


As shown in FIGS. 17B-17C, for example, if the user selects link 1744, the digital assistant instantiates a web browsing process and displays a user interface 1746 (e.g., a snippet or a window) for continuing the flight booking task. In some examples, in response to spoken output 1772, the user provides a speech input 1756 such as “OK” confirming that the user desires to continue flight book using a web browser of user device 1700. Upon receiving speech input 1756, the digital assistant instantiates a web browsing process and displays user interface 1746 (e.g., a snippet or a window) for continuing the flight booking task.


With reference to FIG. 17D, in some embodiments, a digital assistant of a user device 1700 continues to perform a task that was partially performed remotely at a first electronic device. In some embodiments, the digital assistant of the user device continues to perform the task using content received from the first electronic device, rather than a third electronic device such as a server. As illustrated in FIG. 17D, in some examples, the first electronic device (e.g., phone 1720 or tablet 1732) may have been performing a task. For example, the user may have been using phone 1720 to compose an email or using tablet 1732 to edit a document such as a photo. In some examples, the user is interrupted while using phone 1720 or tablet 1732, and/or desires to continue the performance of the task using user device 1700. In some examples, the user may desire to continue the performance of the task simply because using user device 1700 is more convenient (e.g., a larger screen). Accordingly, the user may provide a speech input 1758 such as “Open the document I was just editing” or speech input 1759 such as “Open the email I was just drafting.”


With reference to FIG. 17D, upon receiving speech input 1758 or 1759, the digital assistant determines the user intent is to perform a task of editing a document or composing an email. Similar to those described above, in some examples, the digital assistant further determines that the task is to be performed at user device 1700 based on context information, and determines that the content for performing the task is located remotely. Similar to described above, in some examples, the digital assistant determines, based on context information (e.g., user-specific data), that the content is located remotely at the first electronic device (e.g., at phone 1720 or tablet 1732), rather than at a server. As shown in FIG. 17D, in accordance with the determination that the task is to be performed at the user device 1700 and the content for performing the task is located remotely, the digital assistant receives the content for performing the task. In some examples, the digital assistant receives the at least a portion of the content from phone 1720 (e.g., a smartphone) and/or at least a portion of the content from tablet 1730. After receiving the content from phone 1720 and/or tablet 1732, the digital assistant provides a response at user device 1700, such as displaying a user interface 1748 for the user to continue editing the document and/or displaying a user interface 1749 for the user to continue composing the email. It is appreciated that the digital assistant of user device 1700 can also cause a first electronic device to continue performing a task that was partially performed remotely at the user device 1700. For example, the user may be composing an email on user device 1700 and may need to leave. The user provides a speech input such as “Open the email I was drafting on my phone.” Based on the speech input, the digital assistant determines the user intent is to continue performing the task on phone 1720 and the content is located remotely at the user device 1700. In some examples, the digital assistant provides the content for performing the task to the first electronic device and causes the first electronic device to continue performing the task, similar to those described above.


With reference to FIG. 17E, in some embodiments, continuing to performing a task is based on context information that is shared or synchronized among a plurality of devices including, for example, user device 1700 and first electronic device (e.g., phone 1720). As described, in some examples, the digital assistant determines a user intent based on the speech input and context information. The context information can be stored locally or remotely. For example, as shown in FIG. 17E, the user provides a speech input 1760 such as “What is the weather like in New York?” to phone 1720. A digital assistant of phone 1720 determines the user intent, performs the task to obtain the weather information in New York, and displays the weather information of New York on a user interface of phone 1720. The user subsequently provides a speech input 1761 such as “How about in Los Angeles?” to user device 1700. In some examples, the digital assistant of user device 1700 determines the user intent using context information stored at and/or shared by phone 1720, either directly or through a server. The context information includes, for example, historical user data associated with phone 1720, conversational state, system state, etc. Both the historical user data and conversational state indicate that user was inquiring about weather information. Accordingly, the digital assistant of user device 1700 determines that the user intent is to obtain the weather information in Los Angeles. Based on the user intent, the digital assistant of user device 1700 receives the weather information from, for example, a server, and provides a user interface 1751 displaying the weather information on user device 1710.


6. Exemplary Functions of a Digital Assistant—Voice-Enabled System Configuration Management



FIGS. 18A-18F and 19A-19D illustrate functionalities of providing system configuration information or performing a task in response to a user request by a digital assistant. In some examples, the digital assistant system (e.g., digital assistant system 700) can be implemented by a user device according to various examples. In some examples, the user device, a server (e.g., server 108), or a combination thereof, may implement a digital assistant system (e.g., digital assistant system 700). The user device is implemented using, for example, device 104, 200, or 400. In some examples, the user device is a laptop computer, a desktop computer, or a tablet computer. The user device operates in a multi-tasking environment, such as a desktop environment.


With references to FIGS. 18A-18F and 19A-19D, in some examples, a user device provides various user interfaces (e.g., user interfaces 1810 and 1910). Similar to those described above, the user device displays the various user interfaces on a display and the various user interfaces enable the user to instantiate one or more processes (e.g., system configuration processes).


As shown in FIGS. 18A-18F and 19A-19D, similar to those described above, the user device displays, on a user interface (e.g., user interfaces 1810 and 1910), an affordance (e.g., affordance 1840 and 1940) to facilitate the instantiation of a digital assistant service.


Similar to those described above, in some examples, the digital assistant is instantiated in response to receiving a pre-determined phrase. In some examples, the digital assistant is instantiated in response to receiving a selection of the affordance.


With reference to FIGS. 18A-18F and 19A-19D, in some embodiments, a digital assistant receives one or more speech inputs, such as speech inputs 1852, 1854, 1856, 1858, 1860, 1862, 1952, 1954, 1956, and 1958 from a user. The user provides various speech inputs for the purpose of managing one or more system configurations of the user device. The system configurations can include audio configurations, date and time configurations, dictation configuration, display configurations, input device configurations, notification configurations, printing configurations, security configurations, backup configurations, application configurations, user interface configurations, or the like. To manage audio configurations, a speech input may include “Mute my microphone,” “Turn the volume all the up,” “Turn the volume up 10%,” or the like. To manage date and time configurations, a speech input may include “What is my time zone?”, “Change my time zone to Cupertino Time,” “Add a clock for London time zone,” or the like. To manage dictation configurations, a speech input may include “Turn on dictation,” “Turn off dictation,” “Dictation in Chinese,” “Enable advanced commands,” or the like. To manage display configurations, a speech input may include “Make my screen brighter,” “Increase the contrast my 20%,” “Extend my screen to a second monitor,” “Mirror my display,” or the like. To manage input device configurations, a speech input may include “Connect my Bluetooth keyboard,” “Make my mouse pointer bigger,” or the like. To manage network configurations, a speech input may include “Turn Wi-Fi on,” “Turn Wi-Fi off,” “Which Wi-Fi network am I connected to?”, “Am I connected to my phone?”, or the like. To manage notification configuration, a speech input may include “Turn on Do not Disturb,” “Stop showing me these notifications,” “Show only new emails,” “No alert for text message,” or the like. To manage printing configurations, a speech input may include “Does my printer have enough ink?”, “Is my printer connected?”, or the like. To manage security configurations, a speech input may include “Change password for John's account,” “Turn on firewall,” “Disable cookie,” or the like. To manage backup configurations, a speech input may include “Run backup now,” “Set backup interval to once a month,” “Recover the July 4 backup of last year,” or the like. To manage application configurations, a speech input may include “Change my default web browser to Safari,” “Automatically log in to Messages application each time I sign in,” or the like. To manage user interface configurations, a speech input may include “Change my desktop wallpapers,” “Hide the dock,” “Add Evernote to the Dock,” or the like. Various examples of using speech inputs to manage system configurations are described below in more details.


Similar to those described above, in some examples, the digital assistant receives speech inputs directly from the user at the user device or indirectly through another electronic device that is communicatively connected to the user device.


With reference to FIGS. 18A-18F and 19A-19D, in some embodiments, the digital assistant identifies context information associated with the user device. The context information includes, for example, user-specific data, sensor data, and user device configuration data. In some examples, the user-specific data includes log information indicating user preferences, the history of user's interaction with the user device, or the like. For example, user-specific data indicates the last time the user's system was backed up; and that the user's preferences of a particular Wi-Fi network when several Wi-Fi networks are available or the like. In some examples, the sensor data includes various data collected by a sensor. For example, the sensor data indicates a printer ink level collected by a printer ink level sensor. In some examples, the user device configuration data includes the current and historical device configurations. For example, the user device configuration data indicates that the user device is currently communicatively connected to one or more electronic devices using Bluetooth connections. The electronic devices may include, for example, a smartphone, a set-top box, a tablet, or the like. As described in more detail below, the user device can determine user intent and/or perform one or more processes using the context information.


With reference to FIGS. 18A-18F and 19A-19D, similar to those described above, in response to receiving a speech input, the digital assistant determines a user intent based on the speech input. The digital assistant determines the user intent based on a result of natural language processing. For example, the digital assistant identifies an actionable intent based on the user input, and generates a structured query to represent the identified actionable intent. The structured query includes one or more parameters associated with the actionable intent. The one or more parameters can be used to facilitate the performance of a task based on the actionable intent. For example, based on a speech input such as “Turn the volume up by 10%,” the digital assistant determines that the actionable intent is to adjust the system volume, and the parameters include setting the volume to be 10% higher than the current volume level. In some embodiments, the digital assistant also determines the user intent based on the speech input and context information. For example, the context information may indicate that the current volume of the user device is at 50%. As a result, upon receiving the speech input such as “Turn the volume up by 10%,” the digital assistant determines that the user intent is to increase the volume level to 60%. Determining the user intent based on speech input and context information is described in more detail below in various examples.


In some embodiments, the digital assistant further determines whether the user intent indicates an informational request or a request for performing a task. Various examples of the determination are provided below in more detail with respect to FIGS. 18A-18F and 19A-19D.


With reference to FIG. 18A, in some examples, the user device displays a user interface 1832 associated with performing a task. For example, the task includes composing a meeting invitation. In composing the meeting invitation, the user may desire to know the time zone of the user device so that the meeting invitation can be properly composed. In some examples, the user provides a speech input 1852 to invoke the digital assistant represented by affordance 1840 or 1841. Speech input 1852 includes, for example, “Hey, Assistant.” The user device receives the speech input 1852 and, in response, invokes the digital assistant such that the digital assistant actively monitors subsequent speech inputs. In some examples, the digital assistant provides a spoken output 1872 indicating that it is invoked. For example, spoken output 1872 includes “Go ahead, I am listening.”


With reference to FIG. 18B, in some examples, the user provides a speech input 1854 such as “What is my time zone?” The digital assistant determines that the user intent is to obtain the time zone of the user device. The digital assistant further determines whether the user intent indicates an informational request or a request for performing a task. In some examples, determining whether the user intent indicates an informational request or a request for performing a task includes determining whether the user intent is to vary a system configuration. For example, based on the determination that the user intent is to obtain the time zone of the user device, the digital assistant determines that no system configuration is to be varied. As a result, the digital assistant determines that the user intent indicates an informational request.


In some embodiments, in accordance with a determination that the user intent indicates an informational request, the digital assistant provides a spoken response to the informational request. In some examples, the digital assistant obtains status of one or more system configurations according to the informational request, and provides the spoken response according to the status of one or more system configurations. As shown in FIG. 18B, the digital assistant determines that the user intent is to obtain the time zone of the user device, and this user intent indicates an informational request. Accordingly, the digital assistant obtains the time zone status from the time and date configuration of the user device. The time zone status indicates, for example, the user device is set to the Pacific time zone. Based on the time zone status, the digital assistant provides a spoken output 1874 such as “Your computer is set to Pacific Standard Time.” In some examples, the digital assistant further provides a link associated with the informational request. As illustrated in FIG. 18B, the digital assistant provides a link 1834, enabling the user to further manage the data and time configurations. In some examples, the user uses an input device (e.g., a mouse) to select link 1834. Upon receiving the user's selection of link 1834, the digital assistant instantiates a date and time configuration process and displays an associated date and time configuration user interface. The user can thus use the date and time configuration user interface to further manage the date and time configurations.


With reference to FIG. 18C, in some examples, the user device displays a user interface 1836 associated with performing a task. For example, the task includes playing a video (e.g., ABC.mov). To enhance the experience of watching the video, the user may desire to use a speaker and may want to know whether a Bluetooth speaker is connected. In some examples, the user provides a speech input 1856 such as “Is my Bluetooth speaker connected?” The digital assistant determines that the user intent is to obtain the connection status of the Bluetooth speaker 1820. The digital assistant further determines that obtaining the connection status of the Bluetooth speaker 1820 does not vary any system configuration and therefore is an informational request.


In some embodiments, in accordance with a determination that the user intent indicates an informational request, the digital assistant obtains status of system configurations according to the informational request, and provides the spoken response according to the status of the system configurations. As shown in FIG. 18C, the digital assistant obtains the connection status from the network configuration of the user device. The connection status indicates, for example, user device 1800 is not connected to a Bluetooth speaker 1820. Based on the connection status, the digital assistant provides a spoken output 1876 such as “No, it is not connected, you can check Bluetooth devices in the network configurations.” In some examples, the digital assistant further provides a link associated with the informational request. As illustrated in FIG. 18C, the digital assistant provides a link 1838, enabling the user to further manage the network configurations. In some examples, the user uses an input device (e.g., a mouse) to select link 1838. Upon receiving the user's selection of link 1838, the digital assistant instantiates a network configuration process and displays an associated network configuration user interface. The user can thus use the network configuration user interface to further manage the network configurations.


With reference to FIG. 18D, in some examples, the user device displays a user interface 1842 associated with performing a task. For example, the task includes viewing and/or editing a document. The user may desire to print out the document and may want to know whether a printer 1830 has enough ink for the printing job. In some examples, the user provides a speech input 1858 such as “Does my printer have enough ink?” The digital assistant determines that the user intent is to obtain printer ink level status of the printer. The digital assistant further determines that the obtaining the printer level status does not vary any system configuration and therefore is an informational request.


In some embodiments, in accordance with a determination that the user intent indicates an informational request, the digital assistant obtains status of system configurations according to the informational request, and provides the spoken response according to the status of the system configurations. As shown in FIG. 18D, the digital assistant obtains the printer ink level status from the printing configuration of the user device. The printer ink level status indicates, for example, the printer ink level of printer 1830 is at 50%. Based on the connection status, the digital assistant provides a spoken output 1878 such as “Yes, your printer has enough ink. You can also look up printer supply levels in the printer configurations.” In some examples, the digital assistant further provides a link associated with the informational request. As illustrated in FIG. 18D, the digital assistant provides a link 1844, enabling the user to further manage the printer configurations. In some examples, the user uses an input device (e.g., a mouse) to select link 1844. Upon receiving the user's selection of the link, the digital assistant instantiates a printer configuration process and displays an associated printer configuration user interface. The user can thus use the printer configuration user interface to further manage the printer configurations.


With reference to FIG. 18E, in some examples, the user device displays a user interface 1846 associated with performing a task. For example, the task includes browsing Internet using a web browser (e.g., Safari). To browse the Internet, the user may desire to know available Wi-Fi networks and select one Wi-Fi network to connect. In some examples, the user provides a speech input 1860 such as “Which Wi-Fi networks are available?” The digital assistant determines that the user intent is to obtain a list of available Wi-Fi networks. The digital assistant further determines that obtaining the list of available Wi-Fi networks does not vary any system configuration and therefore is an informational request.


In some embodiments, in accordance with a determination that the user intent indicates an informational request, the digital assistant obtains status of system configurations according to the informational request, and provides the spoken response according to the status of the system configurations. As shown in FIG. 18E, the digital assistant obtains status of currently available Wi-Fi networks from the network configuration of the user device. The status of currently available Wi-Fi networks indicates, for example, Wi-Fi network 1, Wi-Fi network 2, and Wi-Fi network 3 are available. In some examples, the status further indicates the signal strength of each of the Wi-Fi networks. The digital assistant displays a user interface 1845 providing information according to the status. For example, user interface 1845 provides the list of available Wi-Fi networks. The digital assistant also provides a spoken output 1880 such as “Here is a list of available Wi-Fi networks.” In some examples, the digital assistant further provides a link associated with the informational request. As illustrated in FIG. 18E, the digital assistant provides a link 1847, enabling the user to further manage the network configurations. In some examples, the user uses an input device (e.g., a mouse) to select link 1847. Upon receiving the user's selection of the link 1847, the digital assistant instantiates a network configuration process and displays an associated network configuration user interface. The user can thus use the network configuration user interface to further manage the configurations.


With reference to FIG. 18F, in some examples, the user device displays a user interface 1890 associated with performing a task. For example, the task includes preparing a meeting agenda. In preparing a meeting agenda, the user may desire to find a date and time for the meeting. In some examples, the user provides a speech input 1862 such as “Find a time on my calendar for next Tuesday's meeting in the morning.” The digital assistant determines that the user intent is to find an available time slot on the user's calendar on Tuesday morning. The digital assistant further determines that finding a time slot does not vary any system configuration and therefore is an informational request.


In some embodiments, in accordance with a determination that the user intent indicates an informational request, the digital assistant obtains status of system configurations according to the informational request, and provides the spoken response according to the status of the system configurations. As shown in FIG. 18F, the digital assistant obtains status of user's calendar from calendar configurations. The status of user's calendar indicates, for example, 9a.m. or 11a.m. on Tuesday is still available. The digital assistant displays a user interface 1891 providing information according to the status. For example, user interface 1891 provides the user's calendar in the proximity of the date and time the user requested. In some examples, the digital assistant also provides a spoken output 1882 such as “It looks like Tuesday 9a.m. or 11 a.m is available.” In some examples, the digital assistant further provides a link associated with the informational request. As illustrated in FIG. 18F, the digital assistant provides a link 1849, enabling the user to further manage the calendar configurations. In some examples, the user uses an input device (e.g., a mouse) to select link 1849. Upon receiving the user's selection of link 1849, the digital assistant instantiates a calendar configuration process and displays an associated calendar configuration user interface. The user can thus use the calendar configuration user interface to further manage the configurations.


With reference to FIG. 19A, the user device displays a user interface 1932 associated with performing a task. For example, the task includes playing a video (e.g., ABC.mov). While the video is playing, the user may desire to turn up the volume. In some examples, the user provides a speech input 1952 such as “Turn the volume all the way up.” The digital assistant determines that the user intent is to increase the volume to its maximum level. The digital assistant further determines whether the user intent indicates an informational request or a request for performing a task. For example, based on the determination that the user intent is to increase the volume of the user device, the digital assistant determines that an audio configuration is to be varied, and therefore the user intent indicates a request for performing a task.


In some embodiments, in accordance with a determination that the user intent indicates a request for performing a task, the digital assistant instantiates a process associated with the user device to perform the task. Instantiating a process includes invoking the process if the process is not already running. If at least one instance of the process is running, instantiating a process includes executing an existing instance of the process or generating a new instance of the process. For example, instantiating an audio configuration process includes invoking the audio configuration process, using an existing audio configuration process, or generating a new instance of the audio configuration process. In some examples, instantiating a process includes performing the task using the process. For example, as illustrated in FIG. 19A, in accordance with the user intent to increase the volume to its maximum level, the digital assistant instantiates an audio configuration process to set the volume to its maximum level. In some examples, the digital assistant further provides a spoken output 1972 such as “OK, I turned the volume all the way up.”


With reference to FIG. 19B, the user device displays a user interface 1934 associated with performing a task. For example, the task includes viewing or editing a document. The user may desire to lower the screen brightness for eye protection. In some examples, the user provides a speech input 1954 such as “Set my screen brightness to 10% lower.” The digital assistant determines the user intent based on speech input 1954 and context information. For example, context information indicates that the current brightness configuration is at 90%. As a result, the digital assistant determines that the user intent is to reduce the brightness level from 90% to 80%. The digital assistant further determines whether the user intent indicates an informational request or a request for performing a task. For example, based on the determination that the user intent is to change the screen brightness to 80%, the digital assistant determines that a display configuration is to be varied, and therefore the user intent indicates a request for performing a task.


In some embodiments, in accordance with a determination that the user intent indicates a request for performing a task, the digital assistant instantiates a process to perform the task. For example, as illustrated in FIG. 19B, in accordance with the user intent to change the brightness level, the digital assistant instantiates a display configuration process to reduce the brightness level to 80%. In some examples, the digital assistant further provides a spoken output 1974 such as “OK, I turned your screen brightness to 80%.” In some examples, as illustrated in FIG. 19B, the digital assistant provides an affordance 1936 enabling the user to manipulate a result of performing the task. For example, affordance 1936 can be a sliding bar allowing the user to further change the brightness level.


With reference to FIG. 19C, the user device displays a user interface 1938 associated with performing a task. For example, the task includes providing one or more notifications. A notification can include an alert of an email, a message, a reminder, or the like. In some examples, notifications are provided in user interface 1938. A notification can be displayed or provided to the user in real time or shortly after it is available at the user device. For example, a notification appears on user interface 1938 and/or user interface 1910 shorted after the user device receives it. Sometimes, the user may be performing an important task (e.g., editing a document) and may not want to be disturbed by the notifications. In some examples, the user provides a speech input 1956 such as “Don't notify me about incoming emails.” The digital assistant determines that the user intent is to turn off the alert of emails. Based on the determination that the user intent is to turn off the alert of incoming emails, the digital assistant determines that a notification configuration is to be varied, and therefore the user intent indicates a request for performing a task.


In some embodiments, in accordance with a determination that the user intent indicates a request for performing a task, the digital assistant instantiates a process to perform the task. For example, as illustrated in FIG. 19C, in accordance with the user intent, the digital assistant instantiates a notification configuration process to turn off the alert of emails. In some examples, the digital assistant further provides a spoken output 1976 such as “OK, I turned off notifications for mail.” In some examples, as illustrated in FIG. 19C, the digital assistant provides a user interface 1942 (e.g., a snippet or a window) enabling the user to manipulate a result of performing the task. For example, user interface 1942 provides an affordance 1943 (e.g., a cancel button). If the user desires to continue receiving notification of emails, for example, the user can select affordance 1943 to turn the notifications of emails back on. In some examples, the user can also provide another speech input, such as “Notify me of incoming emails” to turn on the notification of emails.


With reference to FIG. 19D, in some embodiments, the digital assistant may not be able to complete a task based on user's speech input and can thus provide a user interface to enable the user to perform the task. As shown in FIG. 19D, in some examples, the user provides a speech input 1958 such as “Show a custom message on my screen saver.” The digital assistant determines that the user intent is to change the screen saver settings to show a custom message. The digital assistant further determines that the user intent is to vary a display configuration, and therefore the user intent indicates a request for performing a task.


In some embodiments, in accordance with a determination that the user intent indicates a request for performing a task, the digital assistant instantiates a process associated with the user device to perform the task. In some examples, if the digital assistant cannot complete the task based on the user intent, it provides a user interface enabling the user to perform the task. For example, based on speech input 1958, the digital assistant may not be able to determine the content of the custom message that is to be shown on the screen saver and therefore cannot complete the task of displaying the custom message. As illustrated in FIG. 19D, in some examples, the digital assistant instantiates a display configuration process and provides a user interface 1946 (e.g., a snippet or a window) to enable the user to manually change the screen saver settings. As another example, the digital assistant provides a link 1944 (e.g., a link to the display configurations) enabling the user to perform the task. The user selects link 1944 by using an input device such as a mouse, a finger, or a stylus. Upon receiving the user's selection, the digital assistant instantiates a display configuration process and displays user interface 1946 to enable the user to change the screen saver settings. In some examples, the digital assistant further provides a spoken output 1978 such as “You can explore screen saver options in the screen saver configurations.”


7. Process for Operating a Digital Assistant—Intelligent Search and Object Management.



FIGS. 20A-20G illustrate a flow diagram of an exemplary process 2000 for operating a digital assistant in accordance with some embodiments. Process 2000 may be performed using one or more devices 104, 108, 200, 400, or 600 (FIG. 1, 2A, 4, or 6A-6B). Operations in process 2000 are, optionally, combined or split, and/or the order of some operations is, optionally, changed.


With reference to FIG. 20A, at block 2002, prior to receiving a first speech input, an affordance to invoke a digital assistant service is displayed on a display associated with a user device. At block 2003, the digital assistant is invoked in response to receiving a pre-determined phrase. At block 2004, the digital assistant is invoked in response to receiving a selection of the affordance.


At block 2006, a first speech input is received from a user. At block 2008, context information associated with the user device is identified. At block 2009, the context information includes at least one of: user-specific data, metadata associated with one or more objects, sensor data, and user device configuration data.


At block 2010, a user intent is determined based on the first speech input and the context information. At block 2012, to determine the user intent, one or more actionable intents are determined. At block 2013, one or more parameters associated with the actionable intent are determined.


With reference to FIG. 20B, at block 2015, it is determined whether the user intent is to perform a task using a searching process or an object managing process. The searching process is configured to search data stored internally or externally to the user device, and the object managing process is configured to manage objects associated with the user device. At block 2016, it is determined whether the speech input includes one or more keywords representing the searching process or the object managing process. At block 2018, it is determined whether the task is associated with searching. At block 2020, in accordance with a determination that the task is associated with searching, it is determined whether performing the task requires the searching process. At block 2021, in accordance with a determination that performing the task does not require the searching process, a spoken request to select the searching process or the object managing process is outputted, and a second speech input is received from the user. The second speech input indicates the selection of the searching process or the object managing process.


At block 2022, in accordance with a determination that performing the task does not require the searching process, it is determined, based on a pre-determined configuration, whether the task is to be performed using the searching process or the object managing process.


With reference to FIG. 20C, at block 2024, in accordance with a determination that the task is not associated with searching, it is determined whether the task is associated with managing at least one object. At block 2025, in accordance with a determination that the task is not associated with managing the at least one object, at least one of the following is performed: determining whether that task can be performed using a fourth process available to the user device and initiating a dialog with the user.


At block 2026, in accordance with a determination the user intent is to perform the task using the searching process, the task is performed using the searching process. At block 2028, at least one object is searched using the searching process. At block 2029, the at least one object includes at least one of a folder or a file. At block 2030, the file includes at least one of a photo, audio, or a video. At block 2031, the file is stored internally or externally to the user device. At block 2032, searching at least one of the folder or the file is based on metadata associated with the folder or the file. At block 2034, the at least one object includes a communication. At block 2035, the communication includes at least one of an email, a message, a notification, or a voicemail. At block 2036, metadata associated with the communication is searched.


With reference to FIG. 20D, at block 2037, the at least one object includes at least one of a contact or a calendar. At block 2038, the at least one object includes an application. At block 2039, the at least one object includes an online informational source.


At block 2040, in accordance with the determination that the user intent is to perform the task using the object managing process, the task is performed using the object managing process. At block 2042, the task is associated with searching, and the at least one object is searched using the object managing process. At block 2043, the at least one object includes at least one of a folder or a file. At block 2044, the file includes at least one of a photo, an audio, or a video. At block 2045, the file is stored internally or externally to the user device. At block 2046, searching at least one of the folder or the file is based on metadata associated with the folder or the file.


At block 2048, the object managing process is instantiated. Instantiating the object managing process includes invoking the object managing process, generating a new instance of the object managing process, or executing an existing instance of the object managing process.


With reference to FIG. 20E, at block 2049, the at least one object is created. At block 2050, the at least one object is stored. At block 2051, the at least one object is compressed. At block 2052, the at least one object is moved from a first physical or virtual storage to a second physical or virtual storage. At block 2053, the at least one object is copied from a first physical or virtual storage to a second physical or virtual storage. At block 2054, the at least one object stored in a physical or virtual storage is deleted. At block 2055, the at least one object stored at a physical or virtual storage is recovered. At block 2056, the at least one object is marked. Marking of the at least one object is at least one of visible or associated with metadata of the at least one object. At block 2057, the at least one object is backup according to a predetermined time period for backing up. At block 2058, the at least one object is shared among one or more electronic devices communicatively connected to the user device.


With reference to FIG. 20F, at block 2060, a response is provided based on a result of performing the task using the searching process or the object managing process. At block 2061, a first user interface is displayed providing the result of performing the task using the searching process or the object managing process. At block 2062, a link associated with the result of performing the task using the searching process is displayed. At block 2063, a spoken output is provided according to the result of performing the task using the searching process or the object managing process.


At block 2064, it is provided an affordance that enables the user to manipulate the result of performing the task using the searching process or the object managing process. At block 2065, it is instantiated a third process that operates using the result of performing the task.


With reference to FIG. 20F, at block 2066, a confidence level is determined. At block 2067, the confidence level represents the accuracy in determining the user intent based on the first speech input and context information associated with the user device. At block 2068, the confidence level represents the accuracy in determining whether the user intent is to perform the task using the searching process or the object managing process.


With reference to FIG. 20G, at block 2069, the confidence level represents the accuracy in performing the task using the searching process or the object managing process.


At block 2070, the response is provided in accordance with the determination of the confidence level. At block 2071, it is determined whether the confidence level is greater than or equal to a threshold confidence level. At block 2072, in accordance with a determination that the confidence level is greater than or equal to the threshold confidence level, a first response is provided. At block 2073, in accordance with a determination that the confidence level is less than a threshold confidence level, a second response is provided.


8. Process for Operating a Digital Assistant—Continuity.



FIGS. 21A-21E illustrate a flow diagram of an exemplary process 2100 for operating a digital assistant in accordance with some embodiments. Process 2100 may be performed using one or more devices 104, 108, 200, 400, 600, 1400, 1500, 1600, or 1700 (FIGS. 1, 2A, 4, 6A-6B, 14A-14D, 15A-15D, 16A-16C, and 17A-17E). Operations in process 2100 are, optionally, combined or split and/or the order of some operations is, optionally, changed.


With reference to FIG. 21A, at block 2102, prior to receiving a first speech input, an affordance to invoke a digital assistant service is displayed on a display associated with a user device. At block 2103, the digital assistant is invoked in response to receiving a pre-determined phrase. At block 2104, the digital assistant is invoked in response to receiving a selection of the affordance.


At block 2106, a first speech input is received from a user to perform a task. At block 2108, context information associated with the user device is identified. At block 2109, the user device is configured to provide a plurality of user interfaces. At block 2110, the user device includes a laptop computer, a desktop computer, or a server. At block 2112, the context information includes at least one of: user-specific data, metadata associated with one or more objects, sensor data, and user device configuration data.


At block 2114, a user intent is determined based on the speech input and the context information. At block 2115, to determine the user intent, one or more actionable intents are determined. At block 2116, one or more parameters associated with the actionable intent are determined.


With reference to FIG. 21B, at block 2118, in accordance with user intent, it is determined whether the task is to be performed at the user device or at a first electronic device communicatively connected to the user device. At block 2120, the first electronic device includes a laptop computer, a desktop computer, a server, a smartphone, a tablet, a set-top box, or a watch. At block 2121, determining whether the task is to be performed at the user device or at the first electronic device is based on one or more keywords included in the speech input. At block 2122, it is determined whether performing the task at the user device satisfies performance criteria. At block 2123, the performance criteria are determined based on one or more user preferences. At block 2124, the performance criteria are determined based on the device configuration data. At block 2125, the performance criteria are dynamically updated. At block 2126, in accordance with a determination that performing the task at the user device satisfies the performance criteria, it is determined that the task is to be performed at the user device.


With reference to FIG. 21C, at block 2128, in accordance with a determination that performing the task at the user device does not satisfy the performance criteria, it is determined whether performing the task at the first electronic device satisfies the performance criteria. At block 2130, in accordance with a determination that performing the task at the first electronic device satisfies the performance criteria, it is determined that the task is to be performed at the first electronic device. At block 2132, in accordance with a determination that performing the task at the first electronic device does not meet the performance criteria, it is determined whether performing the task at the second electronic device satisfies the performance criteria.


At block 2134, in accordance with a determination that the task is to be performed at the user device and content for performing the task is located remotely, the content for performing the task is received. At block 2135, at least a portion of the content is received from the first electronic device. At least a portion of the content is stored in the first electronic device. At block 2136, at least a portion of the content is received from a third electronic device.


With reference to FIG. 21D, at block 2138, in accordance with a determination that the task is to be performed at the first electronic device and the content for performing the task is located remotely to the first electronic device, the content for performing the task is provided to the first electronic device. At block 2139, at least a portion of the content is provided from the user device to the first electronic device. At least a portion of the content is stored at the user device. At block 2140, at least a portion of the content is caused to be provided from a fourth electronic device to the first electronic device. At least a portion of the content is stored at the fourth electronic device.


At block 2142, the task is to be performed at the user device. A first response is provided at the user device using the received content. At block 2144, the task is performed at the user device. At block 2145, performing the task at the user device is a continuation of a task partially performed remotely to the user device. At block 2146, a first user interface is displayed associated with the task to be performed at the user device. At block 2148, a link associated with the task is to be performed at the user device. At block 2150, a spoken output is provided according to the task to be performed at the user device.


With reference to FIG. 21E, at block 2152, the task is to be performed at the first electronic device, and a second response is provided at the user device. At block 2154, the task is to be performed at the first electronic device. At block 2156, the task to be performed at the first electronic device is a continuation of a task performed remotely to the first electronic device. At block 2158, a spoken output is provided according to the task to be performed at the first electronic device. At block 2160, a spoken output is provided according to the task to be performed at the first electronic device.


9. Process for Operating a Digital Assistant—System Configuration Management.



FIGS. 22A-22D illustrate a flow diagram of an exemplary process 2200 for operating a digital assistant in accordance with some embodiments. Process 2200 may be performed using one or more devices 104, 108, 200, 400, 600, or 1800 (FIGS. 1, 2A, 4, 6A-6B, and 18C-18D). Operations in process 2200 are, optionally, combined or split, and/or the order of some operations is, optionally, changed.


With reference to FIG. 22A, at block 2202, prior to receiving a speech input, an affordance to invoke a digital assistant service is displayed on a display associated with a user device. At block 2203, the digital assistant is invoked in response to receiving a pre-determined phrase. At block 2204, the digital assistant is invoked in response to receiving a selection of the affordance.


At block 2206, a speech input is received from a user to manage one or more system configurations of the user device. The user device is configured to concurrently provide a plurality of user interfaces. At block 2207, the one or more system configurations of the user device comprise audio configurations. At block 2208, the one or more system configurations of the user device comprise date and time configurations. At block 2209, the one or more system configurations of the user device comprise dictation configurations. At block 2210, the one or more system configurations of the user device comprise display configurations. At block 2211, the one or more system configurations of the user device comprise input device configurations. At block 2212, the one or more system configurations of the user device comprise network configurations. At block 2213, the one or more system configurations of the user device comprise notification configurations.


With reference to FIG. 22B, at block 2214, the one or more system configurations of the user device comprise printer configurations. At block 2215, the one or more system configurations of the user device comprise security configurations. At block 2216, the one or more system configurations of the user device comprise backup configurations. At block 2217, the one or more system configurations of the user device comprise application configurations. At block 2218, the one or more system configurations of the user device comprise user interface configurations.


At block 2220, context information associated with the user device is identified. At block 2223, the context information comprises at least one of: user-specific data, device configuration data, and sensor data. At block 2224, the user intent is determined based on the speech input and the context information. At block 2225, one or more actionable intents are determined. At block 2226, one or more parameters associated with the actionable intent are determined.


With reference to FIG. 22C, at block 2228, it is determined whether the user intent indicates an informational request or a request for performing a task. At block 2229, it is determined whether the user intent is to vary a system configuration.


At block 2230, in accordance with a determination that the user intent indicates an informational request, a spoken response is provided to the informational request. At block 2231, status of one or more system configurations is obtained according to the informational request. At block 2232, the spoken response is provided according to the status of one or more system configurations.


At block 2234, in addition to providing the spoken response to the informational request, a first user interface is displayed to provide information according to the status of the one or more system configurations. At block 2236, in addition to providing the spoken response to the informational request, a link associated with the informational request is provided.


At block 2238, in accordance with a determination that the user intent indicates a request for performing a task, a process associated with the user device is instantiated to perform the task. At block 2239, the task is performed using the process. At block 2240, a first spoken output is provided according to a result of performing the task.


With reference to FIG. 22D, at block 2242, a second user interface is provided to enable the user to manipulate a result of performing the task. At block 2244, the second user interface comprises a link associated with the result of performing the task.


At block 2246, a third user interface is provided to enable the user to perform the task. At block 2248, the third user interface includes a link enabling the user to perform the task. At block 2250, a second spoken output associated with the third user interface is provided.


10. Electronic Device—Intelligent Search and Object Management



FIG. 23 shows a functional block diagram of electronic device 2300 configured in accordance with the principles of the various described examples, including those described with reference to FIGS. 8A-8F, 9A-9H, 10A-10B, 11A-11F, 12A-12D, 13A-13C, 14A-14D, 15A-15D, 16A-16C, 17A-17E, 18A-18F, and 19A-19D. The functional blocks of the device can be optionally implemented by hardware, software, or a combination of hardware and software to carry out the principles of the various described examples. It is understood by persons of skill in the art that the functional blocks described in FIG. 23 can be optionally combined or separated into sub-blocks to implement the principles of the various described examples. Therefore, the description herein optionally supports any possible combination, separation, or further definition of the functional blocks described herein.


As shown in FIG. 23, electronic device 2300 can include a microphone 2302 and processing unit 2308. In some examples, processing unit 2308 includes a receiving unit 2310, a an identifying unit 2312, a determining unit 2314, a performing unit 2316, a providing unit 2318, an instantiating unit 2320, a displaying unit 2322, an outputting unit 2324, an initiating unit 2326, a searching unit 2328, a generating unit 2330, an executing unit 2332, a creating unit 2334, an instantiating unit 2335, a storing unit 2336, a compressing unit 2338, a copying unit 2340, a deleting unit 2342, a recovering unit 2344, a marking unit 2346, a backing up unit 2348, a sharing unit 2350, a causing unit 2352, and an obtaining unit 2354.


In some examples, the processing unit 2308 is configured to receive (e.g., with the receiving unit 2310) a first speech input from a user; identify (e.g., with the identifying unit 2312) context information associated with the user device; and determine (e.g., with the determining unit 2314) a user intent based on the first speech input and the context information.


In some examples, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) whether the user intent is to perform a task using a searching process or an object managing process. The searching process is configured to search data stored internally or externally to the user device, and the object managing process is configured to manage objects associated with the user device.


In some examples, in accordance with a determination the user intent is to perform the task using the searching process, the processing unit 2308 is configured to perform (e.g., with the performing unit 2316) the task using the searching process. In some examples, in accordance with the determination that the user intent is to perform the task using the object managing process, the processing unit 2308 is configured to perform (e.g., with the performing unit 2316) the task using the object managing process.


In some examples, prior to receiving the first speech input, the processing unit 2308 is configured to display (e.g., with the displaying unit 2322), on a display associated with the user device, an affordance to invoke the digital assistant service.


In some examples, the processing unit 2308 is configured to invoke (e.g., with the invoking unit 2320) the digital assistant in response to receiving a pre-determined phrase.


In some examples, the processing unit 2308 is configured to invoke (e.g., with the invoking unit 2320) the digital assistant in response to receiving a selection of the affordance.


In some examples, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) one or more actionable intents; and determine (e.g., with determining unit 2314) one or more parameters associated with the actionable intent.


In some examples, the context information comprises at least one of: user-specific data, metadata associated with one or more objects, sensor data, and user device configuration data.


In some examples, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) whether the speech input includes one or more keywords representing the searching process or the object managing process.


In some examples, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) whether the task is associated with searching. In accordance with a determination that the task is associated with searching, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) whether performing the task requires the searching process; and in accordance with a determination that the task is not associated with searching, determine (e.g., with the determining unit 2314) whether the task is associated with managing at least one object.


In some examples, the task is associated with searching, and in accordance with a determination that performing the task does not require the searching process, the processing unit 2308 is configured to output (e.g., with the outputting unit 2324) a spoken request to select the searching process or the object managing process and receive (e.g., with the receiving unit 2310), from the user, a second speech input indicating the selection of the searching process or the object managing process.


In some examples, the task is associated with searching, and in accordance with a determination that performing the task does not require the searching process, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314), based on a pre-determined configuration, whether the task is to be performed using the searching process or the object managing process.


In some examples, the task is not associated with searching, and in accordance with a determination that the task is not associated with managing the at least one object, the processing unit 2308 is configured to perform (e.g., with the performing unit 2316) at least one of: determining (e.g., with the determining unit 2314) whether that task can be performed using a fourth process available to the user device; and initiating (e.g., with the initiating unit 2326) dialog with the user.


In some examples, the processing unit 2308 is configured to search (e.g., with the searching unit 2328) at least one object using the searching process.


In some examples, the at least one object includes at least one of a folder or a file. The file includes at least one of a photo, audio, or a video. The file is stored internally or externally to the user device.


In some examples, searching at least one of the folder or the file is based on metadata associated with the folder or the file.


In some examples, the at least one object includes a communication. The communication includes at least one of an email, a message, a notification, or a voicemail.


In some examples, the processing unit 2308 is configured to search (e.g., with the searching unit 2328) metadata associated with the communication.


In some examples, the at least one object includes at least one of a contact or a calendar.


In some examples, the at least one object includes an application.


In some examples, the at least one object includes an online informational source.


In some examples, the task is associated with searching, and the processing unit 2308 is configured to search (e.g., with the searching unit 2328) the at least one object using the object managing process.


In some examples, the at least one object includes at least one of a folder or a file. The file includes at least one of a photo, an audio, or a video. The file is stored internally or externally to the user device.


In some examples, searching at least one of the folder or the file is based on metadata associated with the folder or the file.


In some examples, the processing unit 2308 is configured to instantiate (e.g., with the instantiating unit 2335) the object managing process. Instantiating of the object managing process includes invoking the object managing process, generating a new instance of the object managing process, or executing an existing instance of the object managing process.


In some examples, the processing unit 2308 is configured to create (e.g., with the creating unit 2334) the at least one object.


In some examples, the processing unit 2308 is configured to store (e.g., with the storing unit 2336) the at least one object.


In some examples, the processing unit 2308 is configured to compress (e.g., with the compressing unit 2338) the at least one object.


In some examples, the processing unit 2308 is configured to move (e.g., with the moving unit 2339) the at least one object from a first physical or virtual storage to a second physical or virtual storage.


In some examples, the processing unit 2308 is configured to copy (e.g., with the copying unit 2340) the at least one object from a first physical or virtual storage to a second physical or virtual storage.


In some examples, the processing unit 2308 is configured to delete (e.g., with the deleting unit 2342) the at least one object stored in a physical or virtual storage.


In some examples, the processing unit 2308 is configured to recover (e.g., with the recovering unit 2344) at least one object stored at a physical or virtual storage.


In some examples, the processing unit 2308 is configured to mark (e.g., with the marking unit 2346) the at least one object. Marking of the at least one object is at least one of visible or associated with metadata of the at least one object.


In some examples, the processing unit 2308 is configured to back up (e.g., with the backing up unit 2348) the at least one object according to a predetermined time period for backing up.


In some examples, the processing unit 2308 is configured to share (e.g., with the sharing unit 2350) the at least one object among one or more electronic devices communicatively connected to the user device.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a response based on a result of performing the task using the searching process or the object managing process.


In some examples, the processing unit 2308 is configured to display (e.g., with the displaying unit 2322) a first user interface providing the result of performing the task using the searching process or the object managing process.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a link associated with the result of performing the task using the searching process.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a spoken output according to the result of performing the task using the searching process or the object managing process.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) an affordance that enables the user to manipulate the result of performing the task using the searching process or the object managing process.


In some examples, the processing unit 2308 is configured to instantiate (e.g., with the instantiating unit 2335) a third process that operates using the result of performing the task.


In some examples, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) a confidence level; and provide (e.g., with providing unit 2318) the response in accordance with the determination of the confidence level.


In some examples, the confidence level represents the accuracy in determining the user intent based on the first speech input and context information associated with the user device.


In some examples, the confidence level represents the accuracy in determining whether the user intent is to perform the task using the searching process or the object managing process.


In some examples, the confidence level represents the accuracy in performing the task using the searching process or the object managing process.


In some examples, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) whether the confidence level is greater than or equal to a threshold confidence level. In accordance with a determination that the confidence level is greater than or equal to the threshold confidence level, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a first response; and in accordance with a determination that the confidence level is less than a threshold confidence level, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a second response.


11. Electronic Device—Continuity


In some examples, the processing unit 2308 is configured to receive (e.g., with the receiving unit 2310) a speech input from a user to perform a task; identify (e.g., with the identifying unit 2312) context information associated with the user device; and determine (e.g., with the determining unit 2314) a user intent based on the speech input and context information associated with the user device.


In some examples, the processing unit 2308 is configured to, in accordance with user intent, determine (e.g., with the determining unit 2314) whether the task is to be performed at the user device or at a first electronic device communicatively connected to the user device.


In some examples, in accordance with a determination that the task is to be performed at the user device and content for performing the task is located remotely, the processing unit 2308 is configured to receive (e.g., with the receiving unit 2310) the content for performing the task.


In some examples, in accordance with a determination that the task is to be performed at the first electronic device and the content for performing the task is located remotely to the first electronic device, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) the content for performing the task to the first electronic device.


In some examples, the user device is configured to provide a plurality of user interfaces.


In some examples, the user device includes a laptop computer, a desktop computer, or a server.


In some examples, the first electronic device includes a laptop computer, a desktop computer, a server, a smartphone, a tablet, a set-top box, or a watch.


In some examples, the processing unit 2308 is configured to, prior to receiving the speech input, display (e.g., with the displaying unit 2322), on a display of the user device, an affordance to invoke the digital assistant.


In some examples, the processing unit 2308 is configured to invoke (e.g., with the invoking unit 2320) the digital assistant in response to receiving a pre-determined phrase.


In some examples, the processing unit 2308 is configured to invoke (e.g., with the invoking unit 2320) the digital assistant in response to receiving a selection of the affordance.


In some examples, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) one or more actionable intents; and determine (e.g., with the determining unit 2314) one or more parameters associated with the actionable intent.


In some examples, the context information comprises at least one of: user-specific data, sensor data, and user device configuration data.


In some examples, determining whether the task is to be performed at the user device or at the first electronic device is based on one or more keywords included in the speech input.


In some examples, the processing unit 2308 is configured to determine (e.g., with determining unit 2314) whether performing the task at the user device satisfies performance criteria.


In some examples, in accordance with a determination that performing the task at the user device satisfies the performance criteria, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) that the task is to be performed at the user device.


In some examples, in accordance with a determination that performing the task at the user device does not satisfy the performance criteria, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) whether performing the task at the first electronic device satisfies the performance criteria.


In some examples, in accordance with a determination that performing the task at the first electronic device satisfies the performance criteria, the processing unit 2308 is configured to determine (e.g., with the determining 2314) that the task is to be performed at the first electronic device.


In some examples, in accordance with a determination that the performing the task at the first electronic device does not meet the performance criteria, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) whether performing the task at the second electronic device satisfies the performance criteria.


In some examples, the performance criteria are determined based on one or more user preferences.


In some examples, the performance criteria are determined based on the device configuration data.


In some examples, the performance criteria are dynamically updated.


In some examples, in accordance with a determination that the task is to be performed at the user device and content for performing the task is located remotely, the processing unit 2308 is configured to receive (e.g., with the receiving unit 2310) at least a portion of the content from the first electronic device, wherein at least a portion of the content is stored in the first electronic device.


In some examples, in accordance with a determination that the task is to be performed at the user device and content for performing the task is located remotely, the processing unit 2308 is configured to receive (e.g., with the receiving unit 2310) at least a portion of the content from a third electronic device.


In some examples, in accordance with a determination that the task is to be performed at the first electronic device and the content for performing the task is located remotely to the first electronic device, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) at least a portion of the content from the user device to the first electronic device, wherein at least a portion of the content is stored at the user device.


In some examples, in accordance with a determination that the task is to be performed at the first electronic device and the content for performing the task is located remotely to the first electronic device, the processing unit 2308 is configured to cause (e.g., with the causing unit 2352) at least a portion of the content to be provided from a fourth electronic device to the first electronic device. At least a portion of the content is stored at the fourth electronic device.


In some examples, the task is to be performed at the user device, and processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a first response at the user device using the received content.


In some examples, the processing unit 2308 is configured to perform (e.g., with the performing unit 2316) the task at the user device.


In some examples, performing the task at the user device is a continuation of a task partially performed remotely to the user device.


In some examples, the processing unit 2308 is configured to display (e.g., with the displaying unit 2322) a first user interface associated with the task to be performed at the user device.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a link associated with the task to be performed at the user device.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a spoken output according to the task to be performed at the user device.


In some examples, the task is to be performed at the first electronic device, and the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a second response at the user device.


In some examples, the processing unit 2308 is configured to cause (e.g., with the causing unit 2352) the task to be performed at the first electronic device.


In some examples, the task to be performed at the first electronic device is a continuation of a task performed remotely to the first electronic device.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a spoken output according to the task to be performed at the first electronic device.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) an affordance that enables the user to select another electronic device for performance of the task.


12. Electronic Device—System Configuration Management


In some examples, the processing unit 2308 is configured to receive (e.g., with the receiving unit 2310) a speech input from a user to manage one or more system configurations of the user device. The user device is configured to concurrently provide a plurality of user interfaces.


In some examples, the processing unit 2308 is configured to identify (e.g., with the identifying unit 2312) context information associated with the user device; and determine (e.g., with the determining unit 2314) a user intent based on the speech input and context information.


In some examples, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) whether the user intent indicates an informational request or a request for performing a task.


In some examples, in accordance with a determination that the user intent indicates an informational request, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a spoken response to the informational request.


In some examples, in accordance with a determination that the user intent indicates a request for performing a task, the processing unit 2308 is configured to instantiate (e.g., with the instantiating unit 2335) a process associated with the user device to perform the task.


In some examples, the processing unit 2308 is configured to, prior to receiving the speech input, display (e.g., with the displaying unit 2322) on a display of the user device, an affordance to invoke the digital assistant.


In some examples, the processing unit 2308 is configured to invoke (e.g., with the invoking unit 2320) the digital assistant service in response to receiving a pre-determined phrase.


In some examples, the processing unit 2308 is configured to invoke (e.g., with the invoking unit 2320) the digital assistant service in response to receiving a selection of the affordance.


In some examples, the one or more system configurations of the user device comprise audio configurations.


In some examples, the one or more system configurations of the user device comprise date and time configurations.


In some examples, the one or more system configurations of the user device comprise dictation configurations.


In some examples, the one or more system configurations of the user device comprise display configurations.


In some examples, the one or more system configurations of the user device comprise input device configurations.


In some examples, the one or more system configurations of the user device comprise network configurations.


In some examples, the one or more system configurations of the user device comprise notification configurations.


In some examples, the one or more system configurations of the user device comprise printer configurations.


In some examples, the one or more system configurations of the user device comprise security configurations.


In some examples, the one or more system configurations of the user device comprise backup configurations.


In some examples, the one or more system configurations of the user device comprise application configurations.


In some examples, the one or more system configurations of the user device comprise user interface configurations.


In some examples, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) one or more actionable intents; and determine (e.g., with the determining unit 2314) one or more parameters associated with the actionable intent.


In some examples, the context information comprises at least one of: user-specific data, device configuration data, and sensor data.


In some examples, the processing unit 2308 is configured to determine (e.g., with the determining unit 2314) whether the user intent is to vary a system configuration.


In some examples, the processing unit 2308 is configured to obtain (e.g., with the obtaining unit 2354) status of one or more system configurations according to the informational request; and provide (e.g., with the providing unit 2318) the spoken response according to the status of one or more system configurations.


In some examples, in accordance with a determination that the user intent indicates an informational request, the processing unit 2308 is configured to, in addition to providing the spoken response to the informational request, display (e.g., with the displaying unit 2322) a first user interface providing information according to the status of the one or more system configurations.


In some examples, in accordance with a determination that the user intent indicates an informational request, the processing unit 2308 is configured to, in addition to providing the spoken response to the informational request, provide (e.g., with the providing unit 2318) a link associated with the informational request.


In some examples, in accordance with a determination that the user intent indicates a request for performing a task, the processing unit 2308 is configured to perform (e.g., with the performing unit 2316) the task using the process.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a first spoken output according to a result of performing the task.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a second user interface enabling the user to manipulate a result of performing the task.


In some examples, the second user interface comprises a link associated with the result of performing the task.


In some examples, in accordance with a determination that the user intent indicates a request for performing a task, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a third user interface enabling the user to perform the task.


In some examples, the third user interface includes a link enabling the user to perform the task.


In some examples, the processing unit 2308 is configured to provide (e.g., with the providing unit 2318) a second spoken output associated with the third user interface.


The operation described above with respect to FIG. 23 is, optionally, implemented by components depicted in FIG. 1, 2A, 4, 6A-B, or 7A-7B. For example, receiving operation 2310, identifying operation 2312, determining operation 2314, performing operation 2316, and providing operation 2318 are optionally implemented by processor(s) 220. It would be clear to a person of ordinary skill in the art how other processes can be implemented based on the components depicted in FIG. 1, 2A, 4, 6A-B, or 7A-7B.


It is understood by persons of skill in the art that the functional blocks described in FIG. 23 are, optionally, combined or separated into sub-blocks to implement the principles of the various described embodiments. Therefore, the description herein optionally supports any possible combination or separation or further definition of the functional blocks described herein. For example, processing unit 2308 can have an associated “controller” unit that is operatively coupled with processing unit 2308 to enable operation. This controller unit is not separately illustrated in FIG. 23 but is understood to be within the grasp of one of ordinary skill in the art who is designing a device having a processing unit 2308, such as device 2300. As another example, one or more units, such as the receiving unit 2310, may be hardware units outside of processing unit 2308 in some embodiments. The description herein thus optionally supports combination, separation, and/or further definition of the functional blocks described herein.


The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the techniques and their practical applications. Others skilled in the art are thereby enabled to best utilize the techniques and various embodiments with various modifications as are suited to the particular use contemplated.


Although the disclosure and examples have been fully described with reference to the accompanying drawings, it is to be noted that various changes and modifications will become apparent to those skilled in the art. Such changes and modifications are to be understood as being included within the scope of the disclosure and examples as defined by the claims.

Claims
  • 1. A method for providing a digital assistant service, the method comprising: at a first electronic device with one or more processors and memory: while performing a task, receiving a speech input that requests to perform a continuation of the task at a second electronic device different from the first electronic device, wherein the second electronic device is capable of performing the continuation of the task, and wherein the second electronic device is communicatively connected to the first electronic device;determining a user intent based on the speech input; andin accordance with a determination that the user intent is to perform the continuation of the task at the second electronic device and that content for performing the task is located remotely to the second electronic device: providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device.
  • 2. The method of claim 1, wherein determining the user intent based on the speech input further comprises: determining one or more actionable intents; anddetermining one or more parameters associated with the one or more actionable intents.
  • 3. The method of claim 1, wherein determining the user intent further comprises: identifying context information associated with the second electronic device; anddetermining the user intent based on the speech input and the context information associated with the second electronic device.
  • 4. The method of claim 3, wherein the context information comprises at least one of: user-specific data;sensor data; andsecond electronic device configuration data.
  • 5. The method of claim 1, wherein determining that the user intent is to perform the continuation of the task at the second electronic device further comprises: determining that performing the continuation of the task at the second electronic device satisfies one or more performance criteria.
  • 6. The method of claim 5, further comprising: in accordance with a determination that performing the continuation of the task at the second electronic device does not satisfy the one or more performance criteria, determining whether performing the continuation of the task at the first electronic device satisfies the one or more performance criteria.
  • 7. The method of claim 6, further comprising: in accordance with a determination that performing the continuation of the task at the first electronic device satisfies the one or more performance criteria, determining that the continuation of the task is to be performed at the first electronic device; andin accordance with a determination that the performing the continuation of the task at the first electronic device does not satisfy the one or more performance criteria, determining whether performing the continuation of the task at a third electronic device different from the first electronic device and the second electronic device satisfies the one or more performance criteria.
  • 8. The method of claim 5, wherein the one or more performance criteria are determined based on one or more user preferences.
  • 9. The method of claim 5, wherein the one or more performance criteria are determined based on second electronic device configuration data.
  • 10. The method of claim 5, wherein the one or more performance criteria are dynamically updated.
  • 11. The method of claim 1, wherein providing, to the second electronic device, the content for performing the continuation of the task further comprises: receiving the content from a fourth electronic device; andproviding, to the second electronic device, the content for performing the continuation of the task.
  • 12. The method of claim 1, wherein providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device further comprises: providing a first response at the first electronic device.
  • 13. The method of claim 12, wherein providing the first response at the first electronic device further comprises: displaying a first user interface associated with the continuation of the task to be performed at the second electronic device.
  • 14. The method of claim 1, wherein providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device further comprises: the second electronic device providing a second response.
  • 15. The method of claim 14, wherein the second electronic device providing the second response further comprises: the second electronic device displaying a second user interface associated with the continuation of the task.
  • 16. The method of claim 14, wherein the second electronic device providing the second response further comprises: the second electronic device providing a link associated with the continuation of the task.
  • 17. The method of claim 1, wherein providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device further comprises: the second electronic device performing a portion of the task that has not been performed at the first electronic device using the content provided from the first electronic device.
  • 18. A first electronic device, comprising: one or more processors;memory; andone or more programs stored in memory, the one or more programs including instructions for: while performing a task, receiving a speech input that requests to perform a continuation of the task at a second electronic device different from the first electronic device, wherein the second electronic device is capable of performing the continuation of the task, and wherein the second electronic device is communicatively connected to the first electronic device;determining a user intent based on the speech input; andin accordance with a determination that the user intent is to perform the continuation of the task at the second electronic device and that content for performing the task is located remotely to the second electronic device: providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device.
  • 19. The first electronic device of claim 18, wherein determining the user intent based on the speech input further comprises: determining one or more actionable intents; anddetermining one or more parameters associated with the one or more actionable intents.
  • 20. The first electronic device of claim 18, wherein determining the user intent further comprises: identifying context information associated with the second electronic device; anddetermining the user intent based on the speech input and the context information associated with the second electronic device.
  • 21. The first electronic device of claim 20, wherein the context information comprises at least one of: user-specific data;sensor data; andsecond electronic device configuration data.
  • 22. The first electronic device of claim 18, wherein determining that the user intent is to perform the continuation of the task at the second electronic device further comprises: determining that performing the continuation of the task at the second electronic device satisfies one or more performance criteria.
  • 23. The first electronic device of claim 22, the one or more programs further including instructions for: in accordance with a determination that performing the continuation of the task at the second electronic device does not satisfy the one or more performance criteria, determining whether performing the continuation of the task at the first electronic device satisfies the one or more performance criteria.
  • 24. The first electronic device of claim 23, the one or more programs further including instructions for: in accordance with a determination that performing the continuation of the task at the first electronic device satisfies the one or more performance criteria, determining that the continuation of the task is to be performed at the first electronic device; andin accordance with a determination that the performing the continuation of the task at the first electronic device does not satisfy the one or more performance criteria, determining whether performing the continuation of the task at a third electronic device different from the first electronic device and the second electronic device satisfies the one or more performance criteria.
  • 25. The first electronic device of claim 22, wherein the one or more performance criteria are determined based on one or more user preferences.
  • 26. The first electronic device of claim 22, wherein the one or more performance criteria are determined based on second electronic device configuration data.
  • 27. The first electronic device of claim 22, wherein the one or more performance criteria are dynamically updated.
  • 28. The first electronic device of claim 18, wherein providing, to the second electronic device, the content for performing the continuation of the task further comprises: receiving the content from a fourth electronic device; andproviding, to the second electronic device, the content for performing the continuation of the task.
  • 29. The first electronic device of claim 18, wherein providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device further comprises: providing a first response at the first electronic device.
  • 30. The first electronic device of claim 29, wherein providing the first response at the first electronic device further comprises: displaying a first user interface associated with the continuation of the task to be performed at the second electronic device.
  • 31. The first electronic device of claim 18, wherein providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device further comprises: the second electronic device providing a second response.
  • 32. The first electronic device of claim 31, wherein the second electronic device providing the second response further comprises: the second electronic device displaying a second user interface associated with the continuation of the task.
  • 33. The first electronic device of claim 31, wherein the second electronic device providing the second response further comprises: the second electronic device providing a link associated with the continuation of the task.
  • 34. The first electronic device of claim 18, wherein providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device further comprises: the second electronic device performing a portion of the task that has not been performed at the first electronic device using the content provided from the first electronic device.
  • 35. A non-transitory computer-readable storage medium comprising one or more programs for execution by one or more processors of a first electronic device, the one or more programs including instructions which, when executed by the one or more processors, cause the first electronic device to: while performing a task, receive a speech input that requests to perform a continuation of the task at a second electronic device different from the first electronic device, wherein the second electronic device is capable of performing the continuation of the task, and wherein the second electronic device is communicatively connected to the first electronic device;determine a user intent based on the speech input; andin accordance with a determination that the user intent is to perform the continuation of the task at the second electronic device and that content for performing the task is located remotely to the second electronic device: provide, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device.
  • 36. The non-transitory computer-readable storage medium of claim 35, wherein determining the user intent based on the speech input further comprises: determining one or more actionable intents; anddetermining one or more parameters associated with the one or more actionable intents.
  • 37. The non-transitory computer-readable storage medium of claim 35, wherein determining the user intent further comprises: identifying context information associated with the second electronic device; anddetermining the user intent based on the speech input and the context information associated with the second electronic device.
  • 38. The non-transitory computer-readable storage medium of claim 37, wherein the context information comprises at least one of: user-specific data;sensor data; andsecond electronic device configuration data.
  • 39. The non-transitory computer-readable storage medium of claim 35, wherein determining that the user intent is to perform the continuation of the task at the second electronic device further comprises: determining that performing the continuation of the task at the second electronic device satisfies one or more performance criteria.
  • 40. The non-transitory computer-readable storage medium of claim 39, wherein the one or more programs further comprise instructions, which when executed by the one or more processors, cause the first electronic device to: in accordance with a determination that performing the continuation of the task at the second electronic device does not satisfy the one or more performance criteria, determine whether performing the continuation of the task at the first electronic device satisfies the one or more performance criteria.
  • 41. The non-transitory computer-readable storage medium of claim 40, wherein the one or more programs further comprise instructions, which when executed by the one or more processors, cause the first electronic device to: in accordance with a determination that performing the continuation of the task at the first electronic device satisfies the one or more performance criteria, determine that the continuation of the task is to be performed at the first electronic device; andin accordance with a determination that the performing the continuation of the task at the first electronic device does not satisfy the one or more performance criteria, determine whether performing the continuation of the task at a third electronic device different from the first electronic device and the second electronic device satisfies the one or more performance criteria.
  • 42. The non-transitory computer-readable storage medium of claim 39, wherein the one or more performance criteria are determined based on one or more user preferences.
  • 43. The non-transitory computer-readable storage medium of claim 39, wherein the one or more performance criteria are determined based on second electronic device configuration data.
  • 44. The non-transitory computer-readable storage medium of claim 39, wherein the one or more performance criteria are dynamically updated.
  • 45. The non-transitory computer-readable storage medium of claim 35, wherein providing, to the second electronic device, the content for performing the continuation of the task further comprises: receiving the content from a fourth electronic device; andproviding, to the second electronic device, the content for performing the continuation of the task.
  • 46. The non-transitory computer-readable storage medium of claim 35, wherein providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device further comprises: providing a first response at the first electronic device.
  • 47. The non-transitory computer-readable storage medium of claim 46, wherein providing the first response at the first electronic device further comprises: displaying a first user interface associated with the continuation of the task to be performed at the second electronic device.
  • 48. The non-transitory computer-readable storage medium of claim 35, wherein providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device further comprises: the second electronic device providing a second response.
  • 49. The non-transitory computer-readable storage medium of claim 48, wherein the second electronic device providing the second response further comprises: the second electronic device displaying a second user interface associated with the continuation of the task.
  • 50. The non-transitory computer-readable storage medium of claim 48, wherein the second electronic device providing the second response further comprises: the second electronic device providing a link associated with the continuation of the task.
  • 51. The non-transitory computer-readable storage medium of claim 35, wherein providing, to the second electronic device, the content for performing the continuation of the task, wherein, based on the provided content, the second electronic device performs the continuation of the task based on where the task was previously stopped at the first electronic device further comprises: the second electronic device performing a portion of the task that has not been performed at the first electronic device using the content provided from the first electronic device.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 17/231,713, filed Apr. 15, 2021, entitled “INTELLIGENT DIGITAL ASSISTANT IN A MULTI-TASKING ENVIRONMENT,” which is a continuation of U.S. patent application Ser. No. 16/717,790, filed Dec. 17, 2019, now U.S. Pat. No. 11,037,565, entitled “INTELLIGENT DIGITAL ASSISTANT IN A MULTI-TASKING ENVIRONMENT,” which is a continuation of U.S. patent application Ser. No. 15/271,766, now U.S. Pat. No. 10,586,535, filed Sep. 21, 2016, entitled “INTELLIGENT DIGITAL ASSISTANT IN A MULTI-TASKING ENVIRONMENT,” which claims priority to U.S. Provisional Patent Application Ser. No. 62/348,728, entitled “INTELLIGENT DIGITAL ASSISTANT IN A MULTI-TASKING ENVIRONMENT,” filed on Jun. 10, 2016. The contents of both applications are hereby incorporated by reference in their entirety for all purposes.

US Referenced Citations (3236)
Number Name Date Kind
6233559 Balakrishnan May 2001 B1
6697777 Ho et al. Feb 2004 B1
8345665 Vieri et al. Jan 2013 B2
8346563 Hjelm et al. Jan 2013 B1
8346757 Lamping et al. Jan 2013 B1
8352183 Thota et al. Jan 2013 B2
8352268 Naik et al. Jan 2013 B2
8352272 Rogers et al. Jan 2013 B2
8355919 Silverman et al. Jan 2013 B2
8359234 Vieri Jan 2013 B2
8370145 Endo et al. Feb 2013 B2
8370158 Gazdzinski Feb 2013 B2
8371503 Gazdzinski Feb 2013 B2
8374871 Ehsani et al. Feb 2013 B2
8375320 Kotler et al. Feb 2013 B2
8380504 Peden et al. Feb 2013 B1
8380507 Herman et al. Feb 2013 B2
8381107 Rottler et al. Feb 2013 B2
8381135 Hotelling et al. Feb 2013 B2
8386079 Kohler et al. Feb 2013 B1
8386485 Kerschberg et al. Feb 2013 B2
8386926 Matsuoka et al. Feb 2013 B1
8391844 Novick et al. Mar 2013 B2
8392717 Chai et al. Mar 2013 B2
8396295 Gao et al. Mar 2013 B2
8396714 Rogers et al. Mar 2013 B2
8396715 Odell et al. Mar 2013 B2
8401163 Kirchhoff et al. Mar 2013 B1
8406745 Upadhyay et al. Mar 2013 B1
8407239 Dean et al. Mar 2013 B2
8418086 Weber et al. Apr 2013 B2
8423288 Stahl et al. Apr 2013 B2
8428758 Naik et al. Apr 2013 B2
8433572 Caskey et al. Apr 2013 B2
8433778 Shreesha et al. Apr 2013 B1
8434133 Kulkarni et al. Apr 2013 B2
8442821 Vanhoucke May 2013 B1
8447612 Gazdzinski May 2013 B2
8452597 Bringert et al. May 2013 B2
8452602 Bringert et al. May 2013 B1
8453058 Coccaro et al. May 2013 B1
8457959 Kaiser Jun 2013 B2
8458115 Cai et al. Jun 2013 B2
8458278 Christie et al. Jun 2013 B2
8463592 Lu et al. Jun 2013 B2
8464150 Davidson et al. Jun 2013 B2
8468502 Lui et al. Jun 2013 B2
8473289 Jitkoff et al. Jun 2013 B2
8473485 Wong et al. Jun 2013 B2
8477323 Low et al. Jul 2013 B2
8478816 Parks et al. Jul 2013 B2
8479122 Hotelling et al. Jul 2013 B2
8484027 Murphy Jul 2013 B1
8489599 Bellotti Jul 2013 B2
8498670 Cha et al. Jul 2013 B2
8498857 Kopparapu et al. Jul 2013 B2
8514197 Shahraray et al. Aug 2013 B2
8515736 Duta Aug 2013 B1
8515750 Lei et al. Aug 2013 B1
8521513 Millett et al. Aug 2013 B2
8521526 Lloyd et al. Aug 2013 B1
8521531 Kim Aug 2013 B1
8521533 Ostermann et al. Aug 2013 B1
8527276 Senior et al. Sep 2013 B1
8533266 Koulomzin et al. Sep 2013 B2
8537033 Gueziec Sep 2013 B2
8539342 Lewis Sep 2013 B1
8543375 Hong Sep 2013 B2
8543397 Nguyen Sep 2013 B1
8543398 Strope et al. Sep 2013 B1
8560229 Park et al. Oct 2013 B1
8560366 Mikurak Oct 2013 B2
8571528 Channakeshava Oct 2013 B1
8571851 Tickner et al. Oct 2013 B1
8577683 Dewitt Nov 2013 B2
8583416 Huang et al. Nov 2013 B2
8583511 Hendrickson Nov 2013 B2
8583638 Donelli Nov 2013 B2
8589156 Burke et al. Nov 2013 B2
8589161 Kennewick et al. Nov 2013 B2
8589374 Chaudhari Nov 2013 B2
8589869 Wolfram Nov 2013 B2
8589911 Sharkey et al. Nov 2013 B1
8595004 Koshinaka Nov 2013 B2
8595642 Lagassey Nov 2013 B1
8600743 Lindahl et al. Dec 2013 B2
8600746 Lei et al. Dec 2013 B1
8600930 Sata et al. Dec 2013 B2
8606090 Eyer Dec 2013 B2
8606568 Tickner et al. Dec 2013 B1
8606576 Barr et al. Dec 2013 B1
8606577 Stewart et al. Dec 2013 B1
8615221 Cosenza et al. Dec 2013 B1
8620659 Di Cristo et al. Dec 2013 B2
8620662 Bellegarda Dec 2013 B2
8626681 Jurca et al. Jan 2014 B1
8630841 Van Caldwell et al. Jan 2014 B2
8635073 Chang Jan 2014 B2
8638363 King et al. Jan 2014 B2
8639516 Lindahl et al. Jan 2014 B2
8645128 Agiomyrgiannakis Feb 2014 B1
8645137 Bellegarda et al. Feb 2014 B2
8645138 Weinstein et al. Feb 2014 B1
8654936 Eslambolchi et al. Feb 2014 B1
8655646 Lee et al. Feb 2014 B2
8655901 Li et al. Feb 2014 B1
8660843 Falcon et al. Feb 2014 B2
8660849 Gruber et al. Feb 2014 B2
8660924 Hoch et al. Feb 2014 B2
8660970 Fiedorowicz Feb 2014 B1
8661112 Creamer et al. Feb 2014 B2
8661340 Goldsmith et al. Feb 2014 B2
8670979 Gruber et al. Mar 2014 B2
8675084 Bolton et al. Mar 2014 B2
8676273 Fujisaki Mar 2014 B1
8676583 Gupta et al. Mar 2014 B2
8676904 Lindahl Mar 2014 B2
8677377 Cheyer et al. Mar 2014 B2
8681950 Mack et al. Mar 2014 B2
8682667 Haughay Mar 2014 B2
8687777 Lavian et al. Apr 2014 B1
8688446 Yanagihara Apr 2014 B2
8688453 Joshi et al. Apr 2014 B1
8689135 Portele et al. Apr 2014 B2
8694322 Snitkovskiy et al. Apr 2014 B2
8695074 Saraf et al. Apr 2014 B2
8696364 Cohen Apr 2014 B2
8706472 Ramerth et al. Apr 2014 B2
8706474 Blume et al. Apr 2014 B2
8706503 Cheyer et al. Apr 2014 B2
8707195 Fleizach et al. Apr 2014 B2
8712778 Thenthiruperai Apr 2014 B1
8713119 Lindahl et al. Apr 2014 B2
8713418 King et al. Apr 2014 B2
8719006 Bellegarda May 2014 B2
8719014 Wagner May 2014 B2
8719039 Sharifi May 2014 B1
8731610 Appaji May 2014 B2
8731912 Tickner et al. May 2014 B1
8731942 Cheyer et al. May 2014 B2
8739208 Davis et al. May 2014 B2
8744852 Seymour et al. Jun 2014 B1
8751971 Fleizach et al. Jun 2014 B2
8760537 Johnson et al. Jun 2014 B2
8762145 Ouchi et al. Jun 2014 B2
8762156 Chen Jun 2014 B2
8762469 Lindahl Jun 2014 B2
8768693 Somekh et al. Jul 2014 B2
8768702 Mason et al. Jul 2014 B2
8775154 Clinchant et al. Jul 2014 B2
8775177 Heigold et al. Jul 2014 B1
8775341 Commons Jul 2014 B1
8775931 Fux et al. Jul 2014 B2
8781456 Prociw Jul 2014 B2
8781841 Wang Jul 2014 B1
8793301 Wegenkittl et al. Jul 2014 B2
8798255 Lubowich et al. Aug 2014 B2
8798995 Edara Aug 2014 B1
8799000 Guzzoni et al. Aug 2014 B2
8805684 Aleksic et al. Aug 2014 B1
8805690 Lebeau et al. Aug 2014 B1
8812299 Su Aug 2014 B1
8812302 Xiao et al. Aug 2014 B2
8812321 Gilbert et al. Aug 2014 B2
8823507 Touloumtzis Sep 2014 B1
8823793 Clayton et al. Sep 2014 B2
8825474 Zhai et al. Sep 2014 B1
8831947 Wasserblat et al. Sep 2014 B2
8831949 Smith et al. Sep 2014 B1
8838457 Cerra et al. Sep 2014 B2
8843369 Sharifi Sep 2014 B1
8855915 Furuhata et al. Oct 2014 B2
8861925 Ohme Oct 2014 B1
8862252 Rottler et al. Oct 2014 B2
8868111 Kahn et al. Oct 2014 B1
8868409 Mengibar et al. Oct 2014 B1
8868431 Yamazaki et al. Oct 2014 B2
8868469 Xu et al. Oct 2014 B2
8868529 Lerenc Oct 2014 B2
8880405 Cerra et al. Nov 2014 B2
8886534 Nakano et al. Nov 2014 B2
8886540 Cerra et al. Nov 2014 B2
8886541 Friedlander Nov 2014 B2
8892446 Cheyer et al. Nov 2014 B2
8893023 Perry et al. Nov 2014 B2
8897822 Martin Nov 2014 B2
8898064 Thomas et al. Nov 2014 B1
8898568 Bull et al. Nov 2014 B2
8903716 Chen et al. Dec 2014 B2
8909693 Frissora et al. Dec 2014 B2
8918321 Czahor Dec 2014 B2
8922485 Lloyd Dec 2014 B1
8930176 Li et al. Jan 2015 B2
8930191 Gruber et al. Jan 2015 B2
8938394 Faaborg et al. Jan 2015 B1
8938450 Spivack et al. Jan 2015 B2
8938688 Bradford et al. Jan 2015 B2
8942986 Cheyer et al. Jan 2015 B2
8943423 Merrill et al. Jan 2015 B2
8954440 Gattani et al. Feb 2015 B1
8964947 Noolu et al. Feb 2015 B1
8965770 Petrushin Feb 2015 B2
8972240 Brockett et al. Mar 2015 B2
8972432 Shaw et al. Mar 2015 B2
8972878 Mohler et al. Mar 2015 B2
8976063 Hawkins et al. Mar 2015 B1
8976108 Hawkins et al. Mar 2015 B2
8977255 Freeman et al. Mar 2015 B2
8983383 Haskin Mar 2015 B1
8984098 Tomkins et al. Mar 2015 B1
8989713 Doulton Mar 2015 B2
8990235 King et al. Mar 2015 B2
8994660 Neels et al. Mar 2015 B2
8995972 Cronin Mar 2015 B1
8996350 Dub et al. Mar 2015 B1
8996376 Fleizach et al. Mar 2015 B2
8996381 Mozer et al. Mar 2015 B2
8996550 Ko et al. Mar 2015 B2
8996639 Faaborg et al. Mar 2015 B1
9002714 Kim et al. Apr 2015 B2
9009046 Stewart Apr 2015 B1
9013992 Perkins Apr 2015 B2
9015036 Karov Zangvil et al. Apr 2015 B2
9020804 Barbaiani et al. Apr 2015 B2
9026425 Nikoulina et al. May 2015 B2
9026426 Wu et al. May 2015 B2
9031834 Coorman et al. May 2015 B2
9031970 Das et al. May 2015 B1
9037967 Al-Jefri et al. May 2015 B1
9043208 Koch et al. May 2015 B2
9043211 Haiut et al. May 2015 B2
9043319 Burns et al. May 2015 B1
9046932 Medlock et al. Jun 2015 B2
9049255 Macfarlane et al. Jun 2015 B2
9049295 Cooper et al. Jun 2015 B1
9053706 Jitkoff et al. Jun 2015 B2
9058105 Drory et al. Jun 2015 B2
9058332 Darby et al. Jun 2015 B1
9058811 Wang et al. Jun 2015 B2
9063979 Chiu et al. Jun 2015 B2
9064495 Torok et al. Jun 2015 B1
9065660 Ellis et al. Jun 2015 B2
9070247 Kuhn et al. Jun 2015 B2
9070366 Mathias et al. Jun 2015 B1
9071701 Donaldson et al. Jun 2015 B2
9075435 Noble et al. Jul 2015 B1
9075824 Gordo et al. Jul 2015 B2
9076448 Bennett et al. Jul 2015 B2
9076450 Sadek et al. Jul 2015 B1
9081411 Kalns et al. Jul 2015 B2
9081482 Zhai et al. Jul 2015 B1
9082402 Yadgar et al. Jul 2015 B2
9083581 Addepalli et al. Jul 2015 B1
9092433 Rodriguez Jul 2015 B2
9092789 Anshul Jul 2015 B2
9094576 Karakotsios Jul 2015 B1
9094636 Sanders et al. Jul 2015 B1
9098467 Blanksteen et al. Aug 2015 B1
9101279 Ritchey et al. Aug 2015 B2
9112984 Sejnoha et al. Aug 2015 B2
9117212 Sheets et al. Aug 2015 B2
9117447 Gruber et al. Aug 2015 B2
9123338 Sanders et al. Sep 2015 B1
9143907 Caldwell et al. Sep 2015 B1
9159319 Hoffmeister Oct 2015 B1
9164983 Liu et al. Oct 2015 B2
9171541 Kennewick et al. Oct 2015 B2
9171546 Pike Oct 2015 B1
9172747 Walters et al. Oct 2015 B2
9183845 Gopalakrishnan et al. Nov 2015 B1
9190062 Haughay Nov 2015 B2
9196245 Larcheveque et al. Nov 2015 B2
9197848 Felkai et al. Nov 2015 B2
9201955 Quintao et al. Dec 2015 B1
9202520 Tang Dec 2015 B1
9208153 Zaveri et al. Dec 2015 B1
9213754 Zhan et al. Dec 2015 B1
9214137 Bala et al. Dec 2015 B2
9218122 Thoma et al. Dec 2015 B2
9218809 Bellegard et al. Dec 2015 B2
9218819 Stekkelpa et al. Dec 2015 B1
9223529 Khafizova Dec 2015 B1
9223537 Brown et al. Dec 2015 B2
9230561 Ostermann et al. Jan 2016 B2
9232293 Hanson Jan 2016 B1
9236047 Rasmussen Jan 2016 B2
9241073 Rensburg et al. Jan 2016 B1
9245151 LeBeau et al. Jan 2016 B2
9245388 Poulos et al. Jan 2016 B2
9246984 Zises Jan 2016 B2
9250703 Hernandez-Abrego et al. Feb 2016 B2
9251713 Giovanniello et al. Feb 2016 B1
9251787 Hart et al. Feb 2016 B1
9255812 Maeoka et al. Feb 2016 B2
9257120 Alvarez Guevara et al. Feb 2016 B1
9258604 Bilobrov et al. Feb 2016 B1
9262412 Yang et al. Feb 2016 B2
9262612 Cheyer Feb 2016 B2
9263058 Huang et al. Feb 2016 B2
9274598 Beymer et al. Mar 2016 B2
9280535 Varma et al. Mar 2016 B2
9282211 Osawa Mar 2016 B2
9286727 Kim et al. Mar 2016 B2
9286910 Li et al. Mar 2016 B1
9292487 Weber Mar 2016 B1
9292489 Sak et al. Mar 2016 B1
9292492 Sarikaya et al. Mar 2016 B2
9298358 Wilden et al. Mar 2016 B1
9299344 Braho et al. Mar 2016 B2
9300718 Khanna Mar 2016 B2
9301256 Mohan et al. Mar 2016 B2
9305543 Fleizach et al. Apr 2016 B2
9305548 Kennewick et al. Apr 2016 B2
9311308 Sankarasubramaniam et al. Apr 2016 B2
9311912 Swietlinski et al. Apr 2016 B1
9313317 LeBeau et al. Apr 2016 B1
9318108 Gruber et al. Apr 2016 B2
9325809 Barros et al. Apr 2016 B1
9325842 Siddiqi et al. Apr 2016 B1
9330659 Ju et al. May 2016 B2
9330668 Nanavati et al. May 2016 B2
9330720 Lee May 2016 B2
9335983 Breiner et al. May 2016 B2
9338493 Van Os et al. May 2016 B2
9342829 Zhou et al. May 2016 B2
9342930 Kraft et al. May 2016 B1
9349368 Lebeau et al. May 2016 B1
9355472 Kocienda et al. May 2016 B2
9361084 Costa Jun 2016 B1
9367541 Servan et al. Jun 2016 B1
9368114 Larson et al. Jun 2016 B2
9377865 Berenson et al. Jun 2016 B2
9377871 Waddell et al. Jun 2016 B2
9378456 White et al. Jun 2016 B2
9378740 Rosen et al. Jun 2016 B1
9380155 Reding et al. Jun 2016 B1
9383827 Faaborg et al. Jul 2016 B1
9384185 Medlock et al. Jul 2016 B2
9390726 Smus et al. Jul 2016 B1
9396722 Chung et al. Jul 2016 B2
9400779 Convertino et al. Jul 2016 B2
9401140 Weber et al. Jul 2016 B1
9401147 Jitkoff et al. Jul 2016 B2
9405741 Schaaf et al. Aug 2016 B1
9406224 Sanders et al. Aug 2016 B1
9406299 Gollan et al. Aug 2016 B2
9408182 Hurley et al. Aug 2016 B1
9412392 Lindahl Aug 2016 B2
9418650 Bharadwaj et al. Aug 2016 B2
9423266 Clark et al. Aug 2016 B2
9424246 Spencer et al. Aug 2016 B2
9424840 Hart et al. Aug 2016 B1
9431021 Scalise et al. Aug 2016 B1
9432499 Hajdu et al. Aug 2016 B2
9436918 Pantel et al. Sep 2016 B2
9437186 Liu et al. Sep 2016 B1
9437189 Epstein et al. Sep 2016 B2
9442687 Park et al. Sep 2016 B2
9443527 Watanabe et al. Sep 2016 B1
9454599 Golden et al. Sep 2016 B2
9454957 Mathias et al. Sep 2016 B1
9465798 Lin Oct 2016 B2
9465833 Aravamudan et al. Oct 2016 B2
9465864 Hu et al. Oct 2016 B2
9466027 Byrne et al. Oct 2016 B2
9466121 Yang et al. Oct 2016 B2
9466294 Tunstall-Pedoe et al. Oct 2016 B1
9471566 Zhang et al. Oct 2016 B1
9472196 Wang et al. Oct 2016 B1
9483388 Sankaranarasimhan et al. Nov 2016 B2
9483461 Fleizach et al. Nov 2016 B2
9483529 Pasoi et al. Nov 2016 B1
9484021 Mairesse et al. Nov 2016 B1
9485286 Sellier et al. Nov 2016 B1
9495129 Fleizach et al. Nov 2016 B2
9501741 Cheyer et al. Nov 2016 B2
9502025 Kennewick et al. Nov 2016 B2
9508028 Bannister et al. Nov 2016 B2
9510044 Pereira et al. Nov 2016 B1
9514470 Topatan et al. Dec 2016 B2
9516014 Zafiroglu et al. Dec 2016 B2
9519453 Perkuhn et al. Dec 2016 B2
9524355 Forbes et al. Dec 2016 B2
9529500 Gauci et al. Dec 2016 B1
9531803 Chen et al. Dec 2016 B2
9531862 Vadodaria Dec 2016 B1
9535906 Lee et al. Jan 2017 B2
9536527 Carlson Jan 2017 B1
9536544 Osterman et al. Jan 2017 B2
9547647 Badaskar Jan 2017 B2
9548050 Gruber et al. Jan 2017 B2
9548979 Johnson et al. Jan 2017 B1
9569549 Jenkins et al. Feb 2017 B1
9571995 Scheer et al. Feb 2017 B1
9575964 Yadgar et al. Feb 2017 B2
9576575 Heide Feb 2017 B2
9578173 Sanghavi et al. Feb 2017 B2
9584946 Lyren et al. Feb 2017 B1
9586318 Djugash et al. Mar 2017 B2
9602946 Karkkainen et al. Mar 2017 B2
9607612 Deleeuw Mar 2017 B2
9612999 Prakah-Asante et al. Apr 2017 B2
9619200 Chakladar et al. Apr 2017 B2
9619459 Hebert et al. Apr 2017 B2
9620113 Kennewick et al. Apr 2017 B2
9620126 Chiba Apr 2017 B2
9626695 Balasubramanian et al. Apr 2017 B2
9626799 McArdle et al. Apr 2017 B2
9626955 Fleizach et al. Apr 2017 B2
9633004 Giuli et al. Apr 2017 B2
9633191 Fleizach et al. Apr 2017 B2
9633660 Haughay Apr 2017 B2
9633674 Sinha Apr 2017 B2
9646313 Kim et al. May 2017 B2
9648107 Penilla et al. May 2017 B1
9652453 Mathur et al. May 2017 B2
9658746 Cohn et al. May 2017 B2
9659002 Medlock et al. May 2017 B2
9659298 Lynch et al. May 2017 B2
9665567 Li et al. May 2017 B2
9665662 Gautam et al. May 2017 B1
9668121 Naik et al. May 2017 B2
9672725 Dotan-Cohen et al. Jun 2017 B2
9672822 Brown et al. Jun 2017 B2
9678664 Zhai et al. Jun 2017 B2
9690542 Reddy et al. Jun 2017 B2
9691161 Yalniz et al. Jun 2017 B1
9691378 Meyers et al. Jun 2017 B1
9691384 Wang et al. Jun 2017 B1
9696963 Son et al. Jul 2017 B2
9697016 Jacob Jul 2017 B2
9697822 Naik et al. Jul 2017 B1
9697827 Lilly et al. Jul 2017 B1
9697828 Prasad et al. Jul 2017 B1
9698999 Mutagi Jul 2017 B2
9711148 Sharifi et al. Jul 2017 B1
9720907 Bangalore et al. Aug 2017 B2
9721566 Newendorp et al. Aug 2017 B2
9721570 Beal et al. Aug 2017 B1
9723130 Rand Aug 2017 B2
9734817 Putrycz Aug 2017 B1
9734839 Adams Aug 2017 B1
9741343 Miles et al. Aug 2017 B1
9747083 Roman et al. Aug 2017 B1
9747093 Latino et al. Aug 2017 B2
9754591 Kumar et al. Sep 2017 B1
9755605 Li et al. Sep 2017 B1
9760566 Heck et al. Sep 2017 B2
9767710 Lee et al. Sep 2017 B2
9772994 Karov et al. Sep 2017 B2
9786271 Combs et al. Oct 2017 B1
9792907 Bocklet et al. Oct 2017 B2
9798719 Karov et al. Oct 2017 B2
9812128 Mixter et al. Nov 2017 B2
9813882 Masterman Nov 2017 B1
9818400 Paulik et al. Nov 2017 B2
9823811 Brown et al. Nov 2017 B2
9823828 Zambetti et al. Nov 2017 B2
9824379 Khandelwal et al. Nov 2017 B2
9824691 Montero et al. Nov 2017 B1
9824692 Khoury et al. Nov 2017 B1
9830044 Brown et al. Nov 2017 B2
9830449 Wagner Nov 2017 B1
9842168 Heck et al. Dec 2017 B2
9842584 Hart et al. Dec 2017 B1
9846685 Li Dec 2017 B2
9846836 Gao et al. Dec 2017 B2
9858925 Gruber et al. Jan 2018 B2
9858927 Williams et al. Jan 2018 B2
9886953 Lemay et al. Feb 2018 B2
9887949 Shepherd et al. Feb 2018 B2
9891811 Federighi et al. Feb 2018 B2
9911415 Vanblon et al. Mar 2018 B2
9916839 Scalise et al. Mar 2018 B1
9922642 Pitschel et al. Mar 2018 B2
9928835 Tang Mar 2018 B1
9934777 Joseph et al. Apr 2018 B1
9934785 Hulaud Apr 2018 B1
9940616 Morgan et al. Apr 2018 B1
9946862 Yun et al. Apr 2018 B2
9948728 Linn et al. Apr 2018 B2
9959129 Kannan et al. May 2018 B2
9959506 Karppanen May 2018 B1
9966065 Gruber et al. May 2018 B2
9966068 Cash et al. May 2018 B2
9967381 Kashimba et al. May 2018 B1
9971495 Shetty et al. May 2018 B2
9972304 Paulik et al. May 2018 B2
9984686 Mutagi et al. May 2018 B1
9986419 Naik et al. May 2018 B2
9990129 Yang et al. Jun 2018 B2
9990176 Gray Jun 2018 B1
9990921 Vanblon et al. Jun 2018 B2
9990926 Pearce Jun 2018 B1
9996626 Bailey et al. Jun 2018 B1
9998552 Ledet Jun 2018 B1
10001817 Zambetti et al. Jun 2018 B2
10013416 Bhardwaj et al. Jul 2018 B1
10013654 Levy et al. Jul 2018 B1
10013979 Roma et al. Jul 2018 B1
10019436 Huang Jul 2018 B2
10025378 Venable et al. Jul 2018 B2
10026209 Dagley et al. Jul 2018 B1
10026401 Mutagi et al. Jul 2018 B1
10027662 Mutagi et al. Jul 2018 B1
10032451 Mamkina et al. Jul 2018 B1
10032455 Newman et al. Jul 2018 B2
10037758 Jing et al. Jul 2018 B2
10043516 Saddler et al. Aug 2018 B2
10048748 Sridharan et al. Aug 2018 B2
10049161 Kaneko Aug 2018 B2
10049663 Orr et al. Aug 2018 B2
10049668 Huang et al. Aug 2018 B2
10055390 Sharifi et al. Aug 2018 B2
10055681 Brown et al. Aug 2018 B2
10068570 Dai et al. Sep 2018 B2
10074360 Kim Sep 2018 B2
10074371 Wang et al. Sep 2018 B1
10078487 Gruber et al. Sep 2018 B2
10083213 Podgorny et al. Sep 2018 B1
10083688 Piernot et al. Sep 2018 B2
10083690 Giuli et al. Sep 2018 B2
10088972 Brown et al. Oct 2018 B2
10089072 Piersol et al. Oct 2018 B2
10096319 Jin et al. Oct 2018 B1
10101887 Bernstein et al. Oct 2018 B2
10102359 Cheyer Oct 2018 B2
10115055 Weiss et al. Oct 2018 B2
10127901 Zhao et al. Nov 2018 B2
10127908 Deller et al. Nov 2018 B1
10127926 James Nov 2018 B2
10134425 Johnson, Jr. Nov 2018 B1
10135965 Woolsey et al. Nov 2018 B2
10142222 Zhang Nov 2018 B1
10146923 Pitkänen et al. Dec 2018 B2
10147421 Liddell et al. Dec 2018 B2
10147441 Pogue et al. Dec 2018 B1
10149156 Tiku et al. Dec 2018 B1
10162512 Seo et al. Dec 2018 B2
10162817 Schlesinger et al. Dec 2018 B2
10169329 Futrell et al. Jan 2019 B2
10170123 Orr et al. Jan 2019 B2
10170135 Pearce et al. Jan 2019 B1
10175879 Missig et al. Jan 2019 B2
10176167 Evermann Jan 2019 B2
10176802 Ladhak et al. Jan 2019 B1
10176808 Lovitt et al. Jan 2019 B1
10178301 Welbourne et al. Jan 2019 B1
10185542 Carson et al. Jan 2019 B2
10186254 Williams et al. Jan 2019 B2
10186266 Devaraj et al. Jan 2019 B1
10191627 Cieplinski et al. Jan 2019 B2
10191646 Zambetti et al. Jan 2019 B2
10191718 Rhee et al. Jan 2019 B2
10192546 Piersol et al. Jan 2019 B1
10192552 Raitio et al. Jan 2019 B2
10192557 Lee et al. Jan 2019 B2
10198877 Maltsev et al. Feb 2019 B1
10199051 Binder et al. Feb 2019 B2
10200824 Gross et al. Feb 2019 B2
10204627 Nitz et al. Feb 2019 B2
10210860 Ward et al. Feb 2019 B1
10216351 Yang Feb 2019 B2
10216832 Bangalore et al. Feb 2019 B2
10223066 Martel et al. Mar 2019 B2
10225711 Parks et al. Mar 2019 B2
10228904 Raux Mar 2019 B2
10229109 Cherepanov et al. Mar 2019 B1
10229356 Liu et al. Mar 2019 B1
10229680 Gillespie et al. Mar 2019 B1
10237711 Linn et al. Mar 2019 B2
10241644 Gruber et al. Mar 2019 B2
10242501 Pusch et al. Mar 2019 B1
10248308 Karunamuni et al. Apr 2019 B2
10248771 Ziraknejad et al. Apr 2019 B1
10249300 Booker et al. Apr 2019 B2
10249305 Yu Apr 2019 B2
10255922 Sharifi et al. Apr 2019 B1
10261672 Dolbakian et al. Apr 2019 B1
10261830 Gupta et al. Apr 2019 B2
10269345 Castillo Sanchez et al. Apr 2019 B2
10275513 Cowan et al. Apr 2019 B1
10282737 Clark et al. May 2019 B2
10289205 Sumter et al. May 2019 B1
10291066 Leabman et al. May 2019 B1
10296160 Shah et al. May 2019 B2
10297253 Walker, II et al. May 2019 B2
10303772 Hosn et al. May 2019 B2
10304463 Mixter et al. May 2019 B2
10311482 Baldwin Jun 2019 B2
10311871 Newendorp et al. Jun 2019 B2
10325598 Basye et al. Jun 2019 B2
10331312 Napolitano et al. Jun 2019 B2
10332509 Catanzaro et al. Jun 2019 B2
10332513 D'souza et al. Jun 2019 B1
10332518 Garg et al. Jun 2019 B2
10339224 Fukuoka Jul 2019 B2
10339714 Corso et al. Jul 2019 B2
10339721 Dascola et al. Jul 2019 B1
10339925 Rastrow et al. Jul 2019 B1
10346540 Karov et al. Jul 2019 B2
10346541 Phillips et al. Jul 2019 B1
10346753 Soon-Shiong et al. Jul 2019 B2
10346878 Ostermann et al. Jul 2019 B1
10353975 Oh et al. Jul 2019 B2
10354168 Bluche Jul 2019 B2
10354677 Mohamed et al. Jul 2019 B2
10356243 Sanghavi et al. Jul 2019 B2
10360305 Larcheveque et al. Jul 2019 B2
10360716 Van Der Meulen et al. Jul 2019 B1
10365887 Mulherkar Jul 2019 B1
10366160 Castelli et al. Jul 2019 B2
10366692 Adams et al. Jul 2019 B1
10372814 Gliozzo et al. Aug 2019 B2
10372881 Ingrassia, Jr. et al. Aug 2019 B2
10373381 Nuernberger et al. Aug 2019 B2
10389876 Engelke et al. Aug 2019 B2
10402066 Kawana Sep 2019 B2
10403283 Schramm et al. Sep 2019 B1
10409454 Kagan et al. Sep 2019 B2
10410637 Paulik et al. Sep 2019 B2
10416760 Burns et al. Sep 2019 B2
10417037 Gruber et al. Sep 2019 B2
10417344 Futrell et al. Sep 2019 B2
10417554 Scheffler Sep 2019 B2
10431210 Huang et al. Oct 2019 B1
10437928 Bhaya et al. Oct 2019 B2
10446142 Lim et al. Oct 2019 B2
10453117 Reavely et al. Oct 2019 B1
10469665 Bell et al. Nov 2019 B1
10474961 Brigham et al. Nov 2019 B2
10475446 Gruber et al. Nov 2019 B2
10482875 Henry Nov 2019 B2
10490195 Krishnamoorthy et al. Nov 2019 B1
10496364 Yao Dec 2019 B2
10496705 Irani et al. Dec 2019 B1
10497365 Gruber et al. Dec 2019 B2
10497366 Sapugay et al. Dec 2019 B2
10504518 Irani et al. Dec 2019 B1
10512750 Lewin et al. Dec 2019 B1
10515133 Sharifi Dec 2019 B1
10515623 Grizzel Dec 2019 B1
10521946 Roche et al. Dec 2019 B1
10528386 Yu Jan 2020 B2
10540976 Van Os et al. Jan 2020 B2
10558893 Bluche Feb 2020 B2
10559225 Tao et al. Feb 2020 B1
10559299 Arel et al. Feb 2020 B1
10566007 Fawaz et al. Feb 2020 B2
10568032 Freeman et al. Feb 2020 B2
10572885 Guo et al. Feb 2020 B1
10579401 Dawes Mar 2020 B2
10580409 Walker, II et al. Mar 2020 B2
10582355 Lebeau et al. Mar 2020 B1
10585957 Heck et al. Mar 2020 B2
10586369 Roche et al. Mar 2020 B1
10599449 Chatzipanagiotis et al. Mar 2020 B1
10628483 Rao et al. Apr 2020 B1
10629186 Slifka Apr 2020 B1
10630795 Aoki et al. Apr 2020 B2
10642934 Heck et al. May 2020 B2
10649652 Sun May 2020 B2
10659851 Lister et al. May 2020 B2
10671428 Zeitlin Jun 2020 B2
10679007 Jia et al. Jun 2020 B2
10679608 Mixter et al. Jun 2020 B2
10684099 Zaetterqvist Jun 2020 B2
10684703 Hindi et al. Jun 2020 B2
10699697 Qian et al. Jun 2020 B2
10706841 Gruber et al. Jul 2020 B2
10721190 Zhao et al. Jul 2020 B2
10732708 Roche et al. Aug 2020 B1
10743107 Yoshioka et al. Aug 2020 B1
10748529 Milden Aug 2020 B1
10748546 Kim et al. Aug 2020 B2
10754658 Tamiya Aug 2020 B2
10755032 Douglas et al. Aug 2020 B2
10757499 Vautrin et al. Aug 2020 B1
10769385 Evermann Sep 2020 B2
10776933 Faulkner Sep 2020 B2
10778839 Newstadt et al. Sep 2020 B1
10783151 Bushkin et al. Sep 2020 B1
10783883 Mixter et al. Sep 2020 B2
10789945 Acero et al. Sep 2020 B2
10791176 Phipps et al. Sep 2020 B2
10795944 Brown et al. Oct 2020 B2
10796100 Bangalore et al. Oct 2020 B2
10803255 Dubyak et al. Oct 2020 B2
10811013 Secker-Walker et al. Oct 2020 B1
10818288 Garcia et al. Oct 2020 B2
10831494 Grocutt et al. Nov 2020 B2
10832031 Kienzle et al. Nov 2020 B2
10842968 Kahn et al. Nov 2020 B1
10846618 Ravi et al. Nov 2020 B2
10847142 Newendorp et al. Nov 2020 B2
10860629 Gangadharaiah et al. Dec 2020 B1
10861483 Feinauer et al. Dec 2020 B2
10877637 Antos et al. Dec 2020 B1
10880668 Robinson et al. Dec 2020 B1
10885277 Ravi et al. Jan 2021 B2
10892996 Piersol Jan 2021 B2
10909459 Tsatsin et al. Feb 2021 B2
10937263 Tout et al. Mar 2021 B1
10937410 Rule Mar 2021 B1
10942702 Piersol et al. Mar 2021 B2
10942703 Martel et al. Mar 2021 B2
10944859 Weinstein et al. Mar 2021 B2
10957310 Mohajer et al. Mar 2021 B1
10957311 Solomon et al. Mar 2021 B2
10957337 Chen et al. Mar 2021 B2
10970660 Harris et al. Apr 2021 B1
10974139 Feder et al. Apr 2021 B2
10978056 Challa et al. Apr 2021 B1
10978090 Binder et al. Apr 2021 B2
10983971 Carvalho et al. Apr 2021 B2
11009970 Hindi et al. May 2021 B2
11017766 Chao et al. May 2021 B2
11037565 Kudurshian et al. Jun 2021 B2
11038934 Hansen et al. Jun 2021 B1
11043220 Hansen et al. Jun 2021 B1
11048473 Carson et al. Jun 2021 B2
11061543 Blatz et al. Jul 2021 B1
11072344 Provost et al. Jul 2021 B2
11076039 Weinstein et al. Jul 2021 B2
11080336 Van Dusen Aug 2021 B2
11086858 Koukoumidis et al. Aug 2021 B1
11094311 Candelore et al. Aug 2021 B2
11113598 Socher et al. Sep 2021 B2
11126331 Lo et al. Sep 2021 B2
11132172 Naik et al. Sep 2021 B1
11133008 Piernot et al. Sep 2021 B2
11151899 Pitschel et al. Oct 2021 B2
11169660 Gupta et al. Nov 2021 B2
11181988 Bellegarda et al. Nov 2021 B1
11183193 Hansen et al. Nov 2021 B1
11183205 Ebenezer et al. Nov 2021 B1
11200027 Aggarwal et al. Dec 2021 B2
11204787 Radebaugh et al. Dec 2021 B2
11205192 Rivera et al. Dec 2021 B1
11210477 Srinivasan et al. Dec 2021 B2
11217255 Kim et al. Jan 2022 B2
11235248 Orrino et al. Feb 2022 B1
11269426 Jorasch et al. Mar 2022 B2
11269678 Gruber et al. Mar 2022 B2
11283631 Yan et al. Mar 2022 B2
11289082 Lacy et al. Mar 2022 B1
11418461 Elfardy et al. Aug 2022 B1
11487932 Kramer Nov 2022 B2
11507183 Manjunath et al. Nov 2022 B2
20030115067 Ibaraki et al. Jun 2003 A1
20030167155 Reghetti Sep 2003 A1
20050177359 Lu et al. Aug 2005 A1
20060075429 Istvan et al. Apr 2006 A1
20070150289 Sakuramoto et al. Jun 2007 A1
20070174350 Pell et al. Jul 2007 A1
20080189110 Freeman et al. Aug 2008 A1
20080255852 Hu Oct 2008 A1
20090054046 Whittington et al. Feb 2009 A1
20090225041 Kida et al. Sep 2009 A1
20090306989 Kaji Dec 2009 A1
20090320126 Harada Dec 2009 A1
20100031150 Andrew Feb 2010 A1
20110075818 Vance et al. Mar 2011 A1
20110282686 Venon et al. Nov 2011 A1
20110295590 Lloyd et al. Dec 2011 A1
20120035931 LeBeau et al. Feb 2012 A1
20120041759 Barker et al. Feb 2012 A1
20120084089 Lloyd et al. Apr 2012 A1
20120233553 Barrus Sep 2012 A1
20120265528 Gruber et al. Oct 2012 A1
20120310642 Cao et al. Dec 2012 A1
20130002716 Walker et al. Jan 2013 A1
20130005405 Prociw Jan 2013 A1
20130006633 Grokop et al. Jan 2013 A1
20130006637 Kanevsky et al. Jan 2013 A1
20130006638 Lindahl Jan 2013 A1
20130006957 Huang et al. Jan 2013 A1
20130007240 Qiu et al. Jan 2013 A1
20130007648 Gamon et al. Jan 2013 A1
20130009858 Lacey Jan 2013 A1
20130010575 He et al. Jan 2013 A1
20130013313 Shechtman et al. Jan 2013 A1
20130013319 Grant et al. Jan 2013 A1
20130014026 Beringer et al. Jan 2013 A1
20130014143 Bhatia et al. Jan 2013 A1
20130018659 Chi Jan 2013 A1
20130018863 Regan et al. Jan 2013 A1
20130022189 Ganong et al. Jan 2013 A1
20130024277 Tuchman et al. Jan 2013 A1
20130024576 Dishneau et al. Jan 2013 A1
20130027875 Zhu et al. Jan 2013 A1
20130028404 Omalley et al. Jan 2013 A1
20130030787 Cancedda et al. Jan 2013 A1
20130030789 Dalce Jan 2013 A1
20130030804 Zavaliagkos et al. Jan 2013 A1
20130030815 Madhvanath et al. Jan 2013 A1
20130030904 Aidasani et al. Jan 2013 A1
20130030913 Zhu et al. Jan 2013 A1
20130030955 David Jan 2013 A1
20130031162 Willis et al. Jan 2013 A1
20130031476 Coin et al. Jan 2013 A1
20130176208 Tanaka et al. Jan 2013 A1
20130033643 Kim et al. Feb 2013 A1
20130035086 Chardon et al. Feb 2013 A1
20130035942 Kim et al. Feb 2013 A1
20130035961 Yegnanarayanan Feb 2013 A1
20130035994 Pattan et al. Feb 2013 A1
20130036200 Roberts et al. Feb 2013 A1
20130038437 Talati et al. Feb 2013 A1
20130038618 Urbach Feb 2013 A1
20130041647 Ramerth et al. Feb 2013 A1
20130041654 Walker et al. Feb 2013 A1
20130041661 Lee et al. Feb 2013 A1
20130041665 Jang et al. Feb 2013 A1
20130041667 Longe et al. Feb 2013 A1
20130041685 Yegnanarayanan Feb 2013 A1
20130041968 Cohen et al. Feb 2013 A1
20130046544 Kay et al. Feb 2013 A1
20130047178 Moon et al. Feb 2013 A1
20130050089 Neels et al. Feb 2013 A1
20130054550 Bolohan Feb 2013 A1
20130054609 Rajput et al. Feb 2013 A1
20130054613 Bishop Feb 2013 A1
20130054631 Govani et al. Feb 2013 A1
20130054675 Jenkins et al. Feb 2013 A1
20130054706 Graham et al. Feb 2013 A1
20130054945 Free et al. Feb 2013 A1
20130055099 Yao et al. Feb 2013 A1
20130055147 Vasudev et al. Feb 2013 A1
20130055201 No et al. Feb 2013 A1
20130055402 Amit et al. Feb 2013 A1
20130060571 Soemo et al. Mar 2013 A1
20130060807 Rambhia et al. Mar 2013 A1
20130061139 Mahkovec et al. Mar 2013 A1
20130063611 Papakipos et al. Mar 2013 A1
20130064104 Bekiares et al. Mar 2013 A1
20130066832 Sheehan et al. Mar 2013 A1
20130067307 Tian et al. Mar 2013 A1
20130067312 Rose Mar 2013 A1
20130067421 Osman et al. Mar 2013 A1
20130069769 Pennington et al. Mar 2013 A1
20130073286 Bastea-Forte et al. Mar 2013 A1
20130073293 Jang et al. Mar 2013 A1
20130073346 Chun et al. Mar 2013 A1
20130073580 Mehanna et al. Mar 2013 A1
20130073676 Cockcroft Mar 2013 A1
20130077772 Lichorowic et al. Mar 2013 A1
20130078930 Chen et al. Mar 2013 A1
20130080152 Brun et al. Mar 2013 A1
20130080162 Chang et al. Mar 2013 A1
20130080167 Mozer Mar 2013 A1
20130080177 Chen Mar 2013 A1
20130080178 Kang et al. Mar 2013 A1
20130080251 Dempski Mar 2013 A1
20130080890 Krishnamurthi Mar 2013 A1
20130080972 Moshrefi et al. Mar 2013 A1
20130082967 Hillis et al. Apr 2013 A1
20130084882 Khorashadi et al. Apr 2013 A1
20130085755 Bringert et al. Apr 2013 A1
20130085757 Nakamura et al. Apr 2013 A1
20130085761 Bringert et al. Apr 2013 A1
20130086609 Levy et al. Apr 2013 A1
20130090921 Liu et al. Apr 2013 A1
20130091090 Spivack et al. Apr 2013 A1
20130095805 Lebeau et al. Apr 2013 A1
20130096909 Brun et al. Apr 2013 A1
20130096911 Beaufort et al. Apr 2013 A1
20130096917 Edgar et al. Apr 2013 A1
20130097566 Berglund Apr 2013 A1
20130097682 Zeljkovic et al. Apr 2013 A1
20130100017 Papakipos et al. Apr 2013 A1
20130100268 Mihailidis et al. Apr 2013 A1
20130103383 Du et al. Apr 2013 A1
20130103391 Millmore et al. Apr 2013 A1
20130103405 Namba et al. Apr 2013 A1
20130103698 Schlipf Apr 2013 A1
20130106742 Lee et al. May 2013 A1
20130107053 Ozaki May 2013 A1
20130109412 Nguyen et al. May 2013 A1
20130110505 Gruber et al. May 2013 A1
20130110511 Spiegel et al. May 2013 A1
20130110515 Guzzoni et al. May 2013 A1
20130110518 Gruber et al. May 2013 A1
20130110519 Cheyer et al. May 2013 A1
20130110520 Cheyer et al. May 2013 A1
20130110943 Menon et al. May 2013 A1
20130111330 Staikos et al. May 2013 A1
20130111348 Gruber et al. May 2013 A1
20130111365 Chen et al. May 2013 A1
20130111487 Cheyer et al. May 2013 A1
20130111581 Griffin et al. May 2013 A1
20130115927 Gruber et al. May 2013 A1
20130117022 Chen et al. May 2013 A1
20130124187 Qin May 2013 A1
20130124189 Baldwin May 2013 A1
20130124672 Pan May 2013 A1
20130125168 Agnihotri et al. May 2013 A1
20130130669 Xiao et al. May 2013 A1
20130132081 Ryu et al. May 2013 A1
20130132084 Stonehocker et al. May 2013 A1
20130132089 Fanty et al. May 2013 A1
20130132094 Lim May 2013 A1
20130132871 Zeng et al. May 2013 A1
20130138440 Strope et al. May 2013 A1
20130141551 Kim Jun 2013 A1
20130142317 Reynolds Jun 2013 A1
20130142345 Waldmann Jun 2013 A1
20130144594 Bangalore et al. Jun 2013 A1
20130144616 Bangalore Jun 2013 A1
20130151258 Chandrasekar et al. Jun 2013 A1
20130151339 Kim et al. Jun 2013 A1
20130152092 Yadgar Jun 2013 A1
20130154811 Ferren et al. Jun 2013 A1
20130155948 Pinheiro et al. Jun 2013 A1
20130156198 Kim et al. Jun 2013 A1
20130157629 Lee et al. Jun 2013 A1
20130158977 Senior Jun 2013 A1
20130159847 Banke et al. Jun 2013 A1
20130159861 Rottler et al. Jun 2013 A1
20130165232 Nelson et al. Jun 2013 A1
20130166278 James et al. Jun 2013 A1
20130166303 Chang et al. Jun 2013 A1
20130166332 Hammad Jun 2013 A1
20130166442 Nakajima et al. Jun 2013 A1
20130167242 Paliwal Jun 2013 A1
20130170738 Capuozzo et al. Jul 2013 A1
20130172022 Seymour et al. Jul 2013 A1
20130173258 Liu et al. Jul 2013 A1
20130173268 Weng et al. Jul 2013 A1
20130173513 Chu et al. Jul 2013 A1
20130173610 Hu et al. Jul 2013 A1
20130173614 Ismalon Jul 2013 A1
20130174034 Brown et al. Jul 2013 A1
20130176147 Anderson et al. Jul 2013 A1
20130176244 Yamamoto et al. Jul 2013 A1
20130176592 Sasaki Jul 2013 A1
20130177296 Geisner et al. Jul 2013 A1
20130179168 Bae et al. Jul 2013 A1
20130179172 Nakamura et al. Jul 2013 A1
20130179440 Gordon Jul 2013 A1
20130179806 Bastide et al. Jul 2013 A1
20130183942 Novick et al. Jul 2013 A1
20130183944 Mozer et al. Jul 2013 A1
20130185059 Riccardi Jul 2013 A1
20130185066 Tzirkel-Hancock et al. Jul 2013 A1
20130185074 Gruber et al. Jul 2013 A1
20130185081 Cheyer et al. Jul 2013 A1
20130185336 Singh et al. Jul 2013 A1
20130187850 Schulz et al. Jul 2013 A1
20130187857 Griffin et al. Jul 2013 A1
20130190021 Vieri et al. Jul 2013 A1
20130191117 Atti et al. Jul 2013 A1
20130191408 Volkert Jul 2013 A1
20130197911 Wei et al. Aug 2013 A1
20130197914 Yelvington et al. Aug 2013 A1
20130198159 Hendry Aug 2013 A1
20130198841 Poulson Aug 2013 A1
20130204813 Master et al. Aug 2013 A1
20130204897 McDougall Aug 2013 A1
20130204967 Seo et al. Aug 2013 A1
20130207898 Sullivan et al. Aug 2013 A1
20130210410 Xu Aug 2013 A1
20130210492 You et al. Aug 2013 A1
20130212501 Anderson et al. Aug 2013 A1
20130218553 Fujii et al. Aug 2013 A1
20130218560 Hsiao et al. Aug 2013 A1
20130218574 Falcon et al. Aug 2013 A1
20130218899 Raghavan et al. Aug 2013 A1
20130219333 Palwe et al. Aug 2013 A1
20130222249 Pasquero et al. Aug 2013 A1
20130223279 Tinnakornsrisuphap et al. Aug 2013 A1
20130225128 Gomar Aug 2013 A1
20130226580 Witt-Ehsani Aug 2013 A1
20130226935 Bai et al. Aug 2013 A1
20130226996 Itagaki et al. Aug 2013 A1
20130231917 Naik Sep 2013 A1
20130234947 Kristensson et al. Sep 2013 A1
20130235987 Arroniz-Escobar Sep 2013 A1
20130238312 Waibel Sep 2013 A1
20130238326 Kim et al. Sep 2013 A1
20130238334 Ma et al. Sep 2013 A1
20130238540 O'donoghue et al. Sep 2013 A1
20130238647 Thompson Sep 2013 A1
20130238729 Holzman et al. Sep 2013 A1
20130244615 Miller Sep 2013 A1
20130244633 Jacobs et al. Sep 2013 A1
20130246048 Nagase et al. Sep 2013 A1
20130246050 Yu et al. Sep 2013 A1
20130246329 Pasquero et al. Sep 2013 A1
20130246920 Fields et al. Sep 2013 A1
20130247055 Berner et al. Sep 2013 A1
20130253911 Petri et al. Sep 2013 A1
20130253912 Medlock et al. Sep 2013 A1
20130260739 Saino Oct 2013 A1
20130262168 Makanawala et al. Oct 2013 A1
20130268263 Park et al. Oct 2013 A1
20130268956 Recco Oct 2013 A1
20130275117 Winer Oct 2013 A1
20130275136 Czahor Oct 2013 A1
20130275138 Gruber et al. Oct 2013 A1
20130275164 Gruber et al. Oct 2013 A1
20130275199 Proctor, Jr. et al. Oct 2013 A1
20130275625 Taivalsaari et al. Oct 2013 A1
20130275875 Gruber et al. Oct 2013 A1
20130275899 Schubert et al. Oct 2013 A1
20130279724 Stafford et al. Oct 2013 A1
20130282709 Zhu et al. Oct 2013 A1
20130283168 Brown et al. Oct 2013 A1
20130283199 Selig et al. Oct 2013 A1
20130283283 Wang et al. Oct 2013 A1
20130285913 Griffin et al. Oct 2013 A1
20130288722 Ramanujam et al. Oct 2013 A1
20130289991 Eshwar et al. Oct 2013 A1
20130289993 Rao Oct 2013 A1
20130289994 Newman et al. Oct 2013 A1
20130290001 Yun et al. Oct 2013 A1
20130290222 Gordo et al. Oct 2013 A1
20130290905 Luvogt et al. Oct 2013 A1
20130291015 Pan Oct 2013 A1
20130297078 Kolavennu Nov 2013 A1
20130297198 Velde et al. Nov 2013 A1
20130297317 Lee et al. Nov 2013 A1
20130297319 Kim Nov 2013 A1
20130297348 Cardoza et al. Nov 2013 A1
20130298139 Resnick et al. Nov 2013 A1
20130300645 Fedorov Nov 2013 A1
20130300648 Kim et al. Nov 2013 A1
20130303106 Martin Nov 2013 A1
20130304476 Kim et al. Nov 2013 A1
20130304479 Teller et al. Nov 2013 A1
20130304758 Gruber et al. Nov 2013 A1
20130304815 Puente et al. Nov 2013 A1
20130305119 Kern et al. Nov 2013 A1
20130307855 Lamb et al. Nov 2013 A1
20130307997 O'Keefe et al. Nov 2013 A1
20130308922 Sano et al. Nov 2013 A1
20130311179 Wagner Nov 2013 A1
20130311184 Badavne et al. Nov 2013 A1
20130311487 Moore et al. Nov 2013 A1
20130311997 Gruber et al. Nov 2013 A1
20130315038 Ferren et al. Nov 2013 A1
20130316679 Miller et al. Nov 2013 A1
20130316746 Miller et al. Nov 2013 A1
20130317921 Havas Nov 2013 A1
20130318478 Ogura Nov 2013 A1
20130321267 Bhatti et al. Dec 2013 A1
20130322634 Bennett et al. Dec 2013 A1
20130322665 Bennett et al. Dec 2013 A1
20130325340 Forstall et al. Dec 2013 A1
20130325436 Wang et al. Dec 2013 A1
20130325443 Begeja et al. Dec 2013 A1
20130325447 Levien et al. Dec 2013 A1
20130325448 Levien et al. Dec 2013 A1
20130325460 Kim et al. Dec 2013 A1
20130325473 Larcher et al. Dec 2013 A1
20130325480 Lee et al. Dec 2013 A1
20130325481 Van Os et al. Dec 2013 A1
20130325484 Chakladar et al. Dec 2013 A1
20130325844 Plaisant Dec 2013 A1
20130325967 Parks et al. Dec 2013 A1
20130325970 Roberts et al. Dec 2013 A1
20130325979 Mansfield et al. Dec 2013 A1
20130326576 Zhang et al. Dec 2013 A1
20130328809 Smith Dec 2013 A1
20130329023 Suplee, III et al. Dec 2013 A1
20130331127 Sabatelli et al. Dec 2013 A1
20130332113 Piemonte et al. Dec 2013 A1
20130332159 Federighi et al. Dec 2013 A1
20130332162 Keen Dec 2013 A1
20130332164 Nalk Dec 2013 A1
20130332168 Kim et al. Dec 2013 A1
20130332172 Prakash et al. Dec 2013 A1
20130332400 González Dec 2013 A1
20130332538 Clark et al. Dec 2013 A1
20130332721 Chaudhri et al. Dec 2013 A1
20130332886 Cranfill et al. Dec 2013 A1
20130337771 Klein et al. Dec 2013 A1
20130339028 Rosner et al. Dec 2013 A1
20130339256 Shroff Dec 2013 A1
20130339454 Walker et al. Dec 2013 A1
20130339991 Ricci Dec 2013 A1
20130342487 Jeon Dec 2013 A1
20130342672 Gray et al. Dec 2013 A1
20130343584 Bennett et al. Dec 2013 A1
20130343721 Abecassis Dec 2013 A1
20130346016 Suzuki et al. Dec 2013 A1
20130346065 Davidson et al. Dec 2013 A1
20130346068 Solem et al. Dec 2013 A1
20130346347 Patterson et al. Dec 2013 A1
20130346488 Lunt et al. Dec 2013 A1
20130347018 Limp et al. Dec 2013 A1
20130347029 Tang et al. Dec 2013 A1
20130347102 Shi Dec 2013 A1
20130347117 Parks et al. Dec 2013 A1
20140001255 Anthoine Jan 2014 A1
20140002338 Raffa et al. Jan 2014 A1
20140006012 Zhou et al. Jan 2014 A1
20140006025 Krishnan et al. Jan 2014 A1
20140006027 Kim et al. Jan 2014 A1
20140006028 Hu Jan 2014 A1
20140006030 Fleizach et al. Jan 2014 A1
20140006153 Thangam et al. Jan 2014 A1
20140006191 Shankar et al. Jan 2014 A1
20140006483 Garmark et al. Jan 2014 A1
20140006496 Dearman et al. Jan 2014 A1
20140006562 Handa et al. Jan 2014 A1
20140006947 Garmark et al. Jan 2014 A1
20140006951 Hunter Jan 2014 A1
20140006955 Greenzeiger et al. Jan 2014 A1
20140008163 Mikonaho et al. Jan 2014 A1
20140012574 Pasupalak et al. Jan 2014 A1
20140012575 Ganong et al. Jan 2014 A1
20140012580 Ganong, III et al. Jan 2014 A1
20140012586 Rubin et al. Jan 2014 A1
20140012587 Park Jan 2014 A1
20140013336 Yang Jan 2014 A1
20140019116 Lundberg et al. Jan 2014 A1
20140019133 Bao et al. Jan 2014 A1
20140019460 Sambrani et al. Jan 2014 A1
20140019873 Gupta et al. Jan 2014 A1
20140026037 Garb et al. Jan 2014 A1
20140028029 Jochman Jan 2014 A1
20140028477 Michalske Jan 2014 A1
20140028603 Xie et al. Jan 2014 A1
20140028735 Williams et al. Jan 2014 A1
20140032453 Eustice et al. Jan 2014 A1
20140032678 Koukoumidis et al. Jan 2014 A1
20140033071 Gruber et al. Jan 2014 A1
20140035823 Khoe et al. Feb 2014 A1
20140037075 Bouzid et al. Feb 2014 A1
20140039888 Taubman et al. Feb 2014 A1
20140039893 Weiner et al. Feb 2014 A1
20140039894 Shostak Feb 2014 A1
20140040228 Kritt et al. Feb 2014 A1
20140040274 Aravamudan et al. Feb 2014 A1
20140040748 Lemay et al. Feb 2014 A1
20140040754 Donelli Feb 2014 A1
20140040801 Patel et al. Feb 2014 A1
20140040905 Tsunoda et al. Feb 2014 A1
20140040918 Li Feb 2014 A1
20140040961 Green et al. Feb 2014 A1
20140046922 Crook et al. Feb 2014 A1
20140046934 Zhou et al. Feb 2014 A1
20140047001 Phillips et al. Feb 2014 A1
20140051399 Walker Feb 2014 A1
20140052451 Cheong et al. Feb 2014 A1
20140052680 Nitz et al. Feb 2014 A1
20140052791 Chakra et al. Feb 2014 A1
20140053082 Park Feb 2014 A1
20140053101 Buehler et al. Feb 2014 A1
20140053210 Cheong et al. Feb 2014 A1
20140057610 Olincy et al. Feb 2014 A1
20140058732 Labsky et al. Feb 2014 A1
20140059030 Hakkani-Tur et al. Feb 2014 A1
20140059423 Gorga et al. Feb 2014 A1
20140067361 Nikoulina et al. Mar 2014 A1
20140067371 Liensberger Mar 2014 A1
20140067402 Kim Mar 2014 A1
20140067738 Kingsbury Mar 2014 A1
20140067740 Solari Mar 2014 A1
20140068751 Last Mar 2014 A1
20140071069 Anderson et al. Mar 2014 A1
20140071241 Yang et al. Mar 2014 A1
20140074454 Brown et al. Mar 2014 A1
20140074466 Sharifi et al. Mar 2014 A1
20140074470 Jansche et al. Mar 2014 A1
20140074472 Lin et al. Mar 2014 A1
20140074482 Ohno Mar 2014 A1
20140074483 Van Os Mar 2014 A1
20140074589 Nielsen et al. Mar 2014 A1
20140074815 Plimton Mar 2014 A1
20140074846 Moss et al. Mar 2014 A1
20140075453 Bellessort et al. Mar 2014 A1
20140078065 Akkok Mar 2014 A1
20140079195 Srivastava et al. Mar 2014 A1
20140080410 Jung et al. Mar 2014 A1
20140080428 Rhoads et al. Mar 2014 A1
20140081619 Solntseva et al. Mar 2014 A1
20140081633 Badaskar Mar 2014 A1
20140081635 Yanagihara Mar 2014 A1
20140081829 Milne Mar 2014 A1
20140081941 Bai et al. Mar 2014 A1
20140082500 Wilensky et al. Mar 2014 A1
20140082501 Bae et al. Mar 2014 A1
20140082545 Zhai et al. Mar 2014 A1
20140082715 Grajek et al. Mar 2014 A1
20140086458 Rogers Mar 2014 A1
20140087711 Geyer et al. Mar 2014 A1
20140088952 Fife et al. Mar 2014 A1
20140088961 Woodward et al. Mar 2014 A1
20140088964 Bellegarda Mar 2014 A1
20140088970 Kang Mar 2014 A1
20140092007 Kim et al. Apr 2014 A1
20140095171 Lynch et al. Apr 2014 A1
20140095172 Cabaco et al. Apr 2014 A1
20140095173 Lynch et al. Apr 2014 A1
20140095432 Trumbull et al. Apr 2014 A1
20140095601 Abuelsaad et al. Apr 2014 A1
20140095965 Li Apr 2014 A1
20140096077 Jacob et al. Apr 2014 A1
20140096209 Saraf et al. Apr 2014 A1
20140098247 Rao et al. Apr 2014 A1
20140100847 Ishii et al. Apr 2014 A1
20140101127 Simhon et al. Apr 2014 A1
20140104175 Ouyang et al. Apr 2014 A1
20140108017 Mason et al. Apr 2014 A1
20140108357 Procops et al. Apr 2014 A1
20140108391 Volkert Apr 2014 A1
20140108792 Borzycki et al. Apr 2014 A1
20140112556 Kalinli-Akbacak Apr 2014 A1
20140114554 Lagassey Apr 2014 A1
20140115062 Liu et al. Apr 2014 A1
20140115114 Garmark et al. Apr 2014 A1
20140118155 Bowers et al. May 2014 A1
20140118624 Jang et al. May 2014 A1
20140120961 Buck May 2014 A1
20140122057 Chelba et al. May 2014 A1
20140122059 Patel et al. May 2014 A1
20140122085 Piety et al. May 2014 A1
20140122086 Kapur et al. May 2014 A1
20140122136 Jayanthi May 2014 A1
20140122153 Truitt May 2014 A1
20140122589 Fyke et al. May 2014 A1
20140123022 Lee et al. May 2014 A1
20140128021 Walker et al. May 2014 A1
20140129006 Chen et al. May 2014 A1
20140129226 Lee et al. May 2014 A1
20140132935 Kim et al. May 2014 A1
20140134983 Jung et al. May 2014 A1
20140135036 Bonanni et al. May 2014 A1
20140136013 Wolverton et al. May 2014 A1
20140136187 Wolverton et al. May 2014 A1
20140136195 Abdossalami et al. May 2014 A1
20140136212 Kwon et al. May 2014 A1
20140136946 Matas May 2014 A1
20140136987 Rodriguez May 2014 A1
20140142922 Liang et al. May 2014 A1
20140142923 Jones et al. May 2014 A1
20140142934 Kim May 2014 A1
20140142935 Lindahl et al. May 2014 A1
20140142953 Kim et al. May 2014 A1
20140143550 Ganong, III et al. May 2014 A1
20140143721 Suzuki et al. May 2014 A1
20140143784 Mistry et al. May 2014 A1
20140146200 Scott et al. May 2014 A1
20140148209 Weng et al. May 2014 A1
20140149118 Lee et al. May 2014 A1
20140152577 Yuen et al. Jun 2014 A1
20140153709 Byrd et al. Jun 2014 A1
20140155031 Lee et al. Jun 2014 A1
20140156262 Yuen et al. Jun 2014 A1
20140156269 Lee et al. Jun 2014 A1
20140156279 Okamoto et al. Jun 2014 A1
20140156564 Knight et al. Jun 2014 A1
20140157319 Kimura et al. Jun 2014 A1
20140157422 Livshits et al. Jun 2014 A1
20140163751 Davis et al. Jun 2014 A1
20140163951 Nikoulina et al. Jun 2014 A1
20140163953 Parikh Jun 2014 A1
20140163954 Joshi et al. Jun 2014 A1
20140163962 Castelli et al. Jun 2014 A1
20140163976 Park et al. Jun 2014 A1
20140163977 Hoffmeister et al. Jun 2014 A1
20140163978 Basye et al. Jun 2014 A1
20140163981 Cook et al. Jun 2014 A1
20140163995 Burns et al. Jun 2014 A1
20140164305 Lynch et al. Jun 2014 A1
20140164312 Lynch et al. Jun 2014 A1
20140164476 Thomson Jun 2014 A1
20140164508 Lynch et al. Jun 2014 A1
20140164532 Lynch et al. Jun 2014 A1
20140164533 Lynch et al. Jun 2014 A1
20140164953 Lynch et al. Jun 2014 A1
20140165006 Chaudhri et al. Jun 2014 A1
20140169795 Clough Jun 2014 A1
20140171064 Das Jun 2014 A1
20140172412 Viegas et al. Jun 2014 A1
20140172878 Clark et al. Jun 2014 A1
20140173445 Grassiotto Jun 2014 A1
20140173460 Kim Jun 2014 A1
20140176814 Ahn Jun 2014 A1
20140179295 Luebbers et al. Jun 2014 A1
20140180499 Cooper et al. Jun 2014 A1
20140180689 Kim Jun 2014 A1
20140180697 Torok et al. Jun 2014 A1
20140181123 Tuffet Blaise et al. Jun 2014 A1
20140181703 Sullivan et al. Jun 2014 A1
20140181715 Axelrod et al. Jun 2014 A1
20140181741 Apacible et al. Jun 2014 A1
20140181865 Koganei Jun 2014 A1
20140188335 Madhok et al. Jul 2014 A1
20140188460 Ouyang et al. Jul 2014 A1
20140188477 Zhang Jul 2014 A1
20140188478 Zhang Jul 2014 A1
20140188485 Kim et al. Jul 2014 A1
20140188835 Zhang et al. Jul 2014 A1
20140195226 Yun et al. Jul 2014 A1
20140195230 Han et al. Jul 2014 A1
20140195233 Bapat et al. Jul 2014 A1
20140195244 Cha et al. Jul 2014 A1
20140195251 Zeinstra et al. Jul 2014 A1
20140195252 Gruber et al. Jul 2014 A1
20140198048 Unruh et al. Jul 2014 A1
20140200891 Larcheveque et al. Jul 2014 A1
20140201655 Mahaffey et al. Jul 2014 A1
20140203939 Harrington et al. Jul 2014 A1
20140205076 Kumar et al. Jul 2014 A1
20140207439 Venkatapathy et al. Jul 2014 A1
20140207446 Klein et al. Jul 2014 A1
20140207447 Jiang et al. Jul 2014 A1
20140207466 Smadi Jul 2014 A1
20140207468 Bartnik Jul 2014 A1
20140207582 Flinn et al. Jul 2014 A1
20140211944 Hayward et al. Jul 2014 A1
20140214429 Pantel Jul 2014 A1
20140214537 Yoo et al. Jul 2014 A1
20140215367 Kim et al. Jul 2014 A1
20140215513 Ramer et al. Jul 2014 A1
20140218372 Missig et al. Aug 2014 A1
20140222422 Sarikaya et al. Aug 2014 A1
20140222435 Li et al. Aug 2014 A1
20140222436 Binder et al. Aug 2014 A1
20140222678 Sheets et al. Aug 2014 A1
20140222967 Harrang et al. Aug 2014 A1
20140223377 Shaw et al. Aug 2014 A1
20140223481 Fundament Aug 2014 A1
20140226503 Cooper et al. Aug 2014 A1
20140229158 Zweig et al. Aug 2014 A1
20140229184 Shires Aug 2014 A1
20140230055 Boehl Aug 2014 A1
20140232570 Skinder et al. Aug 2014 A1
20140232656 Pasquero et al. Aug 2014 A1
20140236595 Gray Aug 2014 A1
20140236986 Guzman Aug 2014 A1
20140237042 Ahmed et al. Aug 2014 A1
20140237366 Poulos et al. Aug 2014 A1
20140244248 Arisoy et al. Aug 2014 A1
20140244249 Mohamed et al. Aug 2014 A1
20140244254 Ju et al. Aug 2014 A1
20140244257 Colibro et al. Aug 2014 A1
20140244258 Song et al. Aug 2014 A1
20140244263 Pontual et al. Aug 2014 A1
20140244266 Brown et al. Aug 2014 A1
20140244268 Abdelsamie et al. Aug 2014 A1
20140244270 Han et al. Aug 2014 A1
20140244271 Lindahl Aug 2014 A1
20140244712 Walters et al. Aug 2014 A1
20140245140 Brown et al. Aug 2014 A1
20140247383 Dave et al. Sep 2014 A1
20140247926 Gainsboro et al. Sep 2014 A1
20140249812 Bou-Ghazale et al. Sep 2014 A1
20140249816 Pickering et al. Sep 2014 A1
20140249817 Hart et al. Sep 2014 A1
20140249820 Hsu et al. Sep 2014 A1
20140249821 Kennewick et al. Sep 2014 A1
20140250046 Winn et al. Sep 2014 A1
20140253455 Mauro et al. Sep 2014 A1
20140257809 Goel et al. Sep 2014 A1
20140257815 Zhao et al. Sep 2014 A1
20140257902 Moore et al. Sep 2014 A1
20140258324 Mauro et al. Sep 2014 A1
20140258357 Singh et al. Sep 2014 A1
20140258857 Dykstra-Erickson et al. Sep 2014 A1
20140258905 Lee et al. Sep 2014 A1
20140267022 Kim Sep 2014 A1
20140267599 Drouin et al. Sep 2014 A1
20140267933 Young Sep 2014 A1
20140272821 Pitschel et al. Sep 2014 A1
20140273979 Van Os et al. Sep 2014 A1
20140274005 Luna et al. Sep 2014 A1
20140274203 Ganong, III et al. Sep 2014 A1
20140274211 Sejnoha et al. Sep 2014 A1
20140278051 Mcgavran et al. Sep 2014 A1
20140278343 Tran Sep 2014 A1
20140278349 Grieves et al. Sep 2014 A1
20140278379 Coccaro et al. Sep 2014 A1
20140278390 Kingsbury et al. Sep 2014 A1
20140278391 Braho et al. Sep 2014 A1
20140278394 Bastyr et al. Sep 2014 A1
20140278406 Tsumura et al. Sep 2014 A1
20140278413 Pitschel et al. Sep 2014 A1
20140278426 Jost et al. Sep 2014 A1
20140278429 Ganong, III Sep 2014 A1
20140278435 Ganong, III et al. Sep 2014 A1
20140278436 Khanna et al. Sep 2014 A1
20140278438 Hart et al. Sep 2014 A1
20140278443 Gunn et al. Sep 2014 A1
20140278444 Larson et al. Sep 2014 A1
20140278513 Prakash et al. Sep 2014 A1
20140279622 Lamoureux et al. Sep 2014 A1
20140279739 Elkington et al. Sep 2014 A1
20140279787 Cheng et al. Sep 2014 A1
20140280072 Coleman Sep 2014 A1
20140280107 Heymans et al. Sep 2014 A1
20140280138 Li et al. Sep 2014 A1
20140280292 Skinder Sep 2014 A1
20140280353 Delaney et al. Sep 2014 A1
20140280450 Luna Sep 2014 A1
20140280757 Tran Sep 2014 A1
20140281944 Winer Sep 2014 A1
20140281983 Xian et al. Sep 2014 A1
20140281997 Fleizach et al. Sep 2014 A1
20140282003 Gruber et al. Sep 2014 A1
20140282007 Fleizach Sep 2014 A1
20140282045 Ayanam et al. Sep 2014 A1
20140282178 Borzello et al. Sep 2014 A1
20140282201 Pasquero et al. Sep 2014 A1
20140282203 Pasquero et al. Sep 2014 A1
20140282559 Verduzco et al. Sep 2014 A1
20140282586 Shear et al. Sep 2014 A1
20140282743 Howard et al. Sep 2014 A1
20140288990 Moore et al. Sep 2014 A1
20140289508 Wang Sep 2014 A1
20140297267 Spencer et al. Oct 2014 A1
20140297281 Togawa et al. Oct 2014 A1
20140297284 Gruber et al. Oct 2014 A1
20140297288 Yu et al. Oct 2014 A1
20140298395 Yang et al. Oct 2014 A1
20140304086 Dasdan et al. Oct 2014 A1
20140304605 Ohmura et al. Oct 2014 A1
20140309990 Gandrabur et al. Oct 2014 A1
20140309996 Zhang Oct 2014 A1
20140310001 Kalns et al. Oct 2014 A1
20140310002 Nitz et al. Oct 2014 A1
20140310348 Keskitalo et al. Oct 2014 A1
20140310365 Sample et al. Oct 2014 A1
20140310595 Acharya et al. Oct 2014 A1
20140313007 Harding Oct 2014 A1
20140315492 Woods Oct 2014 A1
20140316585 Boesveld et al. Oct 2014 A1
20140317030 Shen et al. Oct 2014 A1
20140317502 Brown et al. Oct 2014 A1
20140324429 Weilhammer et al. Oct 2014 A1
20140324884 Lindahl et al. Oct 2014 A1
20140330560 Venkatesha et al. Nov 2014 A1
20140330569 Kolavennu et al. Nov 2014 A1
20140330951 Sukoff et al. Nov 2014 A1
20140335823 Heredia et al. Nov 2014 A1
20140337037 Chi Nov 2014 A1
20140337048 Brown et al. Nov 2014 A1
20140337266 Wolverton et al. Nov 2014 A1
20140337370 Aravamudan et al. Nov 2014 A1
20140337371 Li Nov 2014 A1
20140337438 Govande et al. Nov 2014 A1
20140337621 Nakhimov Nov 2014 A1
20140337751 Lim et al. Nov 2014 A1
20140337814 Kalns et al. Nov 2014 A1
20140341217 Eisner et al. Nov 2014 A1
20140342762 Hajdu et al. Nov 2014 A1
20140343834 Demerchant et al. Nov 2014 A1
20140343943 Al-telmissani Nov 2014 A1
20140343946 Torok et al. Nov 2014 A1
20140344205 Luna et al. Nov 2014 A1
20140344627 Schaub et al. Nov 2014 A1
20140344687 Durham et al. Nov 2014 A1
20140347181 Luna et al. Nov 2014 A1
20140350847 Ichinokawa Nov 2014 A1
20140350924 Zurek et al. Nov 2014 A1
20140350933 Bak et al. Nov 2014 A1
20140351741 Medlock et al. Nov 2014 A1
20140351760 Skory et al. Nov 2014 A1
20140358519 Mirkin et al. Dec 2014 A1
20140358521 Mikutel et al. Dec 2014 A1
20140358523 Sheth et al. Dec 2014 A1
20140358549 O'connor et al. Dec 2014 A1
20140359456 Thiele et al. Dec 2014 A1
20140359637 Yan Dec 2014 A1
20140359709 Nassar et al. Dec 2014 A1
20140361973 Raux et al. Dec 2014 A1
20140363074 Dolfing et al. Dec 2014 A1
20140364149 Marti et al. Dec 2014 A1
20140365209 Evermann Dec 2014 A1
20140365214 Bayley Dec 2014 A1
20140365216 Gruber et al. Dec 2014 A1
20140365226 Sinha Dec 2014 A1
20140365227 Cash et al. Dec 2014 A1
20140365407 Brown et al. Dec 2014 A1
20140365505 Clark et al. Dec 2014 A1
20140365880 Bellegarda Dec 2014 A1
20140365885 Carson et al. Dec 2014 A1
20140365895 Magahern et al. Dec 2014 A1
20140365922 Yang Dec 2014 A1
20140365945 Karunamuni et al. Dec 2014 A1
20140370817 Luna Dec 2014 A1
20140370841 Roberts et al. Dec 2014 A1
20140372112 Xue et al. Dec 2014 A1
20140372356 Bilal et al. Dec 2014 A1
20140372468 Collins et al. Dec 2014 A1
20140372931 Zhai et al. Dec 2014 A1
20140379326 Sarikaya et al. Dec 2014 A1
20140379334 Fry Dec 2014 A1
20140379338 Fry Dec 2014 A1
20140379341 Seo et al. Dec 2014 A1
20140379798 Bunner et al. Dec 2014 A1
20140380214 Huang et al. Dec 2014 A1
20140380285 Gabel et al. Dec 2014 A1
20150003797 Schmidt Jan 2015 A1
20150004958 Wang et al. Jan 2015 A1
20150005009 Tomkins et al. Jan 2015 A1
20150006147 Schmidt Jan 2015 A1
20150006148 Goldszmit et al. Jan 2015 A1
20150006157 Silva et al. Jan 2015 A1
20150006167 Kato et al. Jan 2015 A1
20150006176 Pogue et al. Jan 2015 A1
20150006178 Peng et al. Jan 2015 A1
20150006184 Marti et al. Jan 2015 A1
20150006199 Snider et al. Jan 2015 A1
20150012271 Peng et al. Jan 2015 A1
20150012862 Ikeda et al. Jan 2015 A1
20150019219 Tzirkel-Hancock et al. Jan 2015 A1
20150019221 Lee et al. Jan 2015 A1
20150019445 Glass et al. Jan 2015 A1
20150019944 Kalgi Jan 2015 A1
20150019954 Dalal et al. Jan 2015 A1
20150019974 Doi et al. Jan 2015 A1
20150025405 Vairavan et al. Jan 2015 A1
20150025890 Jagatheesan et al. Jan 2015 A1
20150026620 Kwon et al. Jan 2015 A1
20150027178 Scalisi Jan 2015 A1
20150031416 Labowicz et al. Jan 2015 A1
20150032443 Karov et al. Jan 2015 A1
20150032457 Koo et al. Jan 2015 A1
20150033130 Scheessele Jan 2015 A1
20150033219 Breiner et al. Jan 2015 A1
20150033275 Natani et al. Jan 2015 A1
20150034855 Shen Feb 2015 A1
20150038161 Jakobson et al. Feb 2015 A1
20150039292 Suleman et al. Feb 2015 A1
20150039295 Soschen Feb 2015 A1
20150039299 Weinstein et al. Feb 2015 A1
20150039305 Huang Feb 2015 A1
20150039606 Salaka et al. Feb 2015 A1
20150040012 Faaborg et al. Feb 2015 A1
20150042640 Algreatly Feb 2015 A1
20150045003 Vora et al. Feb 2015 A1
20150045007 Cash Feb 2015 A1
20150045068 Soffer et al. Feb 2015 A1
20150046375 Mandel et al. Feb 2015 A1
20150046434 Lim et al. Feb 2015 A1
20150046537 Rakib Feb 2015 A1
20150046828 Desai et al. Feb 2015 A1
20150049884 Ye Feb 2015 A1
20150050633 Christmas et al. Feb 2015 A1
20150050923 Tu et al. Feb 2015 A1
20150051754 Kwon et al. Feb 2015 A1
20150051901 Stonehouse et al. Feb 2015 A1
20150053779 Adamek et al. Feb 2015 A1
20150053781 Nelson et al. Feb 2015 A1
20150055879 Yang Feb 2015 A1
20150058013 Pakhomov et al. Feb 2015 A1
20150058018 Georges et al. Feb 2015 A1
20150058720 Smadja et al. Feb 2015 A1
20150058785 Ookawara Feb 2015 A1
20150065149 Russell et al. Mar 2015 A1
20150065200 Namgung et al. Mar 2015 A1
20150066473 Jeong et al. Mar 2015 A1
20150066479 Pasupalak et al. Mar 2015 A1
20150066494 Salvador et al. Mar 2015 A1
20150066496 Deoras et al. Mar 2015 A1
20150066506 Romano et al. Mar 2015 A1
20150066516 Nishikawa et al. Mar 2015 A1
20150066817 Slayton et al. Mar 2015 A1
20150067485 Kim et al. Mar 2015 A1
20150067819 Shribman et al. Mar 2015 A1
20150067822 Randall Mar 2015 A1
20150071121 Patil et al. Mar 2015 A1
20150073788 Sak et al. Mar 2015 A1
20150073804 Senior et al. Mar 2015 A1
20150074524 Nicholson et al. Mar 2015 A1
20150074615 Han et al. Mar 2015 A1
20150081295 Yun et al. Mar 2015 A1
20150082180 Ames et al. Mar 2015 A1
20150082229 Ouyang et al. Mar 2015 A1
20150086174 Abecassis et al. Mar 2015 A1
20150088511 Bharadwaj et al. Mar 2015 A1
20150088514 Typrin Mar 2015 A1
20150088518 Kim et al. Mar 2015 A1
20150088522 Hendrickson et al. Mar 2015 A1
20150088523 Schuster Mar 2015 A1
20150088998 Isensee et al. Mar 2015 A1
20150092520 Robison et al. Apr 2015 A1
20150094834 Vega et al. Apr 2015 A1
20150095031 Conkie et al. Apr 2015 A1
20150095159 Kennewick et al. Apr 2015 A1
20150095268 Greenzeiger et al. Apr 2015 A1
20150095278 Flinn et al. Apr 2015 A1
20150095310 Beaurepaire Apr 2015 A1
20150100144 Lee et al. Apr 2015 A1
20150100313 Sharma Apr 2015 A1
20150100316 Williams et al. Apr 2015 A1
20150100537 Grieves et al. Apr 2015 A1
20150100983 Pan Apr 2015 A1
20150106061 Yang et al. Apr 2015 A1
20150106085 Lindahl Apr 2015 A1
20150106093 Weeks et al. Apr 2015 A1
20150106737 Montoy-Wilson et al. Apr 2015 A1
20150112684 Scheffer et al. Apr 2015 A1
20150113407 Hoffert et al. Apr 2015 A1
20150113435 Phillips Apr 2015 A1
20150113454 Mclaughlin Apr 2015 A1
20150120296 Stern et al. Apr 2015 A1
20150120641 Soon-Shiong et al. Apr 2015 A1
20150120723 Deshmukh et al. Apr 2015 A1
20150121216 Brown et al. Apr 2015 A1
20150121227 Peng Apr 2015 A1
20150123898 Kim et al. May 2015 A1
20150127336 Lei et al. May 2015 A1
20150127337 Heigold et al. May 2015 A1
20150127348 Follis May 2015 A1
20150127350 Agiomyrgiannakis May 2015 A1
20150128058 Anajwala May 2015 A1
20150130716 Sridharan et al. May 2015 A1
20150133049 Lee et al. May 2015 A1
20150133109 Freeman et al. May 2015 A1
20150134318 Cuthbert et al. May 2015 A1
20150134322 Cuthbert et al. May 2015 A1
20150134323 Cuthbert et al. May 2015 A1
20150134334 Sachidanandam et al. May 2015 A1
20150135085 Shoham et al. May 2015 A1
20150135123 Carr et al. May 2015 A1
20150140934 Abdurrahman et al. May 2015 A1
20150140990 Kim et al. May 2015 A1
20150141150 Zha May 2015 A1
20150142420 Sarikaya et al. May 2015 A1
20150142438 Dai et al. May 2015 A1
20150142440 Parkinson et al. May 2015 A1
20150142447 Kennewick et al. May 2015 A1
20150142851 Gupta et al. May 2015 A1
20150143419 Bhagwat et al. May 2015 A1
20150148013 Baldwin et al. May 2015 A1
20150149146 Abramovitz et al. May 2015 A1
20150149177 Kalns et al. May 2015 A1
20150149182 Kalns et al. May 2015 A1
20150149354 McCoy May 2015 A1
20150149469 Xu et al. May 2015 A1
20150149899 Bernstein et al. May 2015 A1
20150149964 Bernstein et al. May 2015 A1
20150154001 Knox et al. Jun 2015 A1
20150154185 Waibel Jun 2015 A1
20150154976 Mutagi Jun 2015 A1
20150160635 Schofield et al. Jun 2015 A1
20150160855 Bi Jun 2015 A1
20150161108 Back Jun 2015 A1
20150161291 Gur et al. Jun 2015 A1
20150161370 North et al. Jun 2015 A1
20150161521 Shah et al. Jun 2015 A1
20150161989 Hsu et al. Jun 2015 A1
20150161997 Wetsel et al. Jun 2015 A1
20150162000 Di Censo et al. Jun 2015 A1
20150162001 Kar et al. Jun 2015 A1
20150162006 Kummer Jun 2015 A1
20150163558 Wheatley Jun 2015 A1
20150169081 Neels et al. Jun 2015 A1
20150169195 Choi Jun 2015 A1
20150169284 Quast et al. Jun 2015 A1
20150169336 Harper et al. Jun 2015 A1
20150169696 Krishnappa et al. Jun 2015 A1
20150170073 Baker Jun 2015 A1
20150170664 Doherty et al. Jun 2015 A1
20150172262 Ortiz, Jr. et al. Jun 2015 A1
20150172463 Quast et al. Jun 2015 A1
20150177945 Sengupta et al. Jun 2015 A1
20150178388 Winnemoeller et al. Jun 2015 A1
20150178785 Salonen Jun 2015 A1
20150179168 Hakkani-Tur et al. Jun 2015 A1
20150179176 Ryu et al. Jun 2015 A1
20150181285 Zhang et al. Jun 2015 A1
20150185718 Tappan et al. Jul 2015 A1
20150185964 Stout Jul 2015 A1
20150185993 Wheatley et al. Jul 2015 A1
20150185996 Brown et al. Jul 2015 A1
20150186012 Coleman et al. Jul 2015 A1
20150186110 Kannan Jul 2015 A1
20150186154 Brown et al. Jul 2015 A1
20150186155 Brown et al. Jul 2015 A1
20150186156 Brown et al. Jul 2015 A1
20150186351 Hicks et al. Jul 2015 A1
20150186538 Yan et al. Jul 2015 A1
20150186783 Byrne et al. Jul 2015 A1
20150186892 Zhang et al. Jul 2015 A1
20150187355 Parkinson et al. Jul 2015 A1
20150187369 Dadu et al. Jul 2015 A1
20150189362 Lee et al. Jul 2015 A1
20150193379 Mehta Jul 2015 A1
20150193391 Khvostichenko et al. Jul 2015 A1
20150193392 Greenblatt et al. Jul 2015 A1
20150194152 Katuri et al. Jul 2015 A1
20150194165 Faaborg et al. Jul 2015 A1
20150195379 Zhang et al. Jul 2015 A1
20150195606 McDevitt Jul 2015 A1
20150199077 Zuger et al. Jul 2015 A1
20150199960 Huo et al. Jul 2015 A1
20150199965 Leak et al. Jul 2015 A1
20150199967 Reddy et al. Jul 2015 A1
20150200879 Wu et al. Jul 2015 A1
20150201064 Bells et al. Jul 2015 A1
20150201077 Konig et al. Jul 2015 A1
20150205425 Kuscher et al. Jul 2015 A1
20150205568 Matsuoka Jul 2015 A1
20150205632 Gaster Jul 2015 A1
20150205858 Xie et al. Jul 2015 A1
20150206529 Kwon et al. Jul 2015 A1
20150208226 Kuusilinna et al. Jul 2015 A1
20150212791 Kumar et al. Jul 2015 A1
20150213140 Volkert Jul 2015 A1
20150213796 Waltermann et al. Jul 2015 A1
20150215258 Nowakowski et al. Jul 2015 A1
20150215350 Slayton et al. Jul 2015 A1
20150217870 Mccullough et al. Aug 2015 A1
20150220264 Lewis et al. Aug 2015 A1
20150220507 Mohajer et al. Aug 2015 A1
20150220715 Kim et al. Aug 2015 A1
20150220972 Subramanya et al. Aug 2015 A1
20150221302 Han et al. Aug 2015 A1
20150221304 Stewart Aug 2015 A1
20150221307 Shah et al. Aug 2015 A1
20150222586 Ebersman et al. Aug 2015 A1
20150224848 Eisenhour Aug 2015 A1
20150227505 Morimoto Aug 2015 A1
20150227633 Shapira Aug 2015 A1
20150228274 Leppanen et al. Aug 2015 A1
20150228275 Watanabe et al. Aug 2015 A1
20150228281 Raniere Aug 2015 A1
20150228282 Evrard Aug 2015 A1
20150228283 Ehsani et al. Aug 2015 A1
20150228292 Goldstein et al. Aug 2015 A1
20150230095 Smith et al. Aug 2015 A1
20150234556 Shaofeng et al. Aug 2015 A1
20150234636 Barnes, Jr. Aug 2015 A1
20150234800 Ehlen et al. Aug 2015 A1
20150235434 Miller et al. Aug 2015 A1
20150235540 Verna et al. Aug 2015 A1
20150237301 Shi et al. Aug 2015 A1
20150242091 Lu et al. Aug 2015 A1
20150242385 Bao et al. Aug 2015 A1
20150243278 Kibre et al. Aug 2015 A1
20150243279 Morse et al. Aug 2015 A1
20150243283 Halash et al. Aug 2015 A1
20150244665 Choi et al. Aug 2015 A1
20150245154 Dadu et al. Aug 2015 A1
20150248494 Mital Sep 2015 A1
20150248651 Akutagawa et al. Sep 2015 A1
20150248886 Sarikaya et al. Sep 2015 A1
20150249715 Helvik et al. Sep 2015 A1
20150253146 Annapureddy et al. Sep 2015 A1
20150253885 Kagan et al. Sep 2015 A1
20150254057 Klein et al. Sep 2015 A1
20150254058 Klein et al. Sep 2015 A1
20150254333 Fife et al. Sep 2015 A1
20150255068 Kim et al. Sep 2015 A1
20150255071 Chiba Sep 2015 A1
20150256873 Klein et al. Sep 2015 A1
20150261298 Li Sep 2015 A1
20150261496 Faaborg et al. Sep 2015 A1
20150261850 Mittal Sep 2015 A1
20150261944 Hosom et al. Sep 2015 A1
20150262443 Chong Sep 2015 A1
20150262573 Brooks et al. Sep 2015 A1
20150262583 Kanda et al. Sep 2015 A1
20150269139 McAteer et al. Sep 2015 A1
20150269420 Kim et al. Sep 2015 A1
20150269617 Mikurak Sep 2015 A1
20150269677 Milne Sep 2015 A1
20150269943 VanBlon et al. Sep 2015 A1
20150277574 Jain et al. Oct 2015 A1
20150278199 Hazen et al. Oct 2015 A1
20150278348 Paruchuri et al. Oct 2015 A1
20150278370 Stratvert et al. Oct 2015 A1
20150278737 Chen Huebscher et al. Oct 2015 A1
20150279354 Gruenstein et al. Oct 2015 A1
20150279358 Kingsbury et al. Oct 2015 A1
20150279360 Mengibar et al. Oct 2015 A1
20150279366 Krestnikov et al. Oct 2015 A1
20150281380 Wang et al. Oct 2015 A1
20150281401 Le et al. Oct 2015 A1
20150286627 Chang et al. Oct 2015 A1
20150286716 Snibbe et al. Oct 2015 A1
20150286937 Hildebrand Oct 2015 A1
20150287401 Lee et al. Oct 2015 A1
20150287408 Svendsen et al. Oct 2015 A1
20150287409 Jang Oct 2015 A1
20150287411 Kojima et al. Oct 2015 A1
20150288629 Choi et al. Oct 2015 A1
20150293602 Kay et al. Oct 2015 A1
20150294086 Kare et al. Oct 2015 A1
20150294377 Chow Oct 2015 A1
20150294516 Chiang Oct 2015 A1
20150294670 Roblek et al. Oct 2015 A1
20150295915 Xiu Oct 2015 A1
20150296065 Narita et al. Oct 2015 A1
20150301796 Visser et al. Oct 2015 A1
20150302316 Buryak et al. Oct 2015 A1
20150302855 Kim et al. Oct 2015 A1
20150302856 Kim et al. Oct 2015 A1
20150302857 Yamada Oct 2015 A1
20150302870 Burke et al. Oct 2015 A1
20150308470 Graham et al. Oct 2015 A1
20150309691 Seo et al. Oct 2015 A1
20150309997 Lee et al. Oct 2015 A1
20150310114 Ryger et al. Oct 2015 A1
20150310852 Spizzo et al. Oct 2015 A1
20150310858 Li et al. Oct 2015 A1
20150310862 Dauphin et al. Oct 2015 A1
20150310879 Buchanan et al. Oct 2015 A1
20150310888 Chen Oct 2015 A1
20150312182 Langholz Oct 2015 A1
20150312409 Czarnecki et al. Oct 2015 A1
20150314454 Breazeal et al. Nov 2015 A1
20150317069 Clements et al. Nov 2015 A1
20150317310 Eiche et al. Nov 2015 A1
20150319264 Allen et al. Nov 2015 A1
20150319411 Kasmir et al. Nov 2015 A1
20150324041 Varley et al. Nov 2015 A1
20150324334 Lee et al. Nov 2015 A1
20150324362 Glass et al. Nov 2015 A1
20150331664 Osawa et al. Nov 2015 A1
20150331711 Huang et al. Nov 2015 A1
20150332667 Mason Nov 2015 A1
20150334346 Cheatham, III et al. Nov 2015 A1
20150339049 Kasemset et al. Nov 2015 A1
20150339391 Kang et al. Nov 2015 A1
20150340033 Di Fabbrizio et al. Nov 2015 A1
20150340034 Schalkwyk et al. Nov 2015 A1
20150340040 Mun et al. Nov 2015 A1
20150340042 Sejnoha et al. Nov 2015 A1
20150341717 Song et al. Nov 2015 A1
20150346845 Di Censo et al. Dec 2015 A1
20150347086 Liedholm et al. Dec 2015 A1
20150347381 Bellegarda Dec 2015 A1
20150347382 Dolfing et al. Dec 2015 A1
20150347383 Willmore et al. Dec 2015 A1
20150347385 Flor et al. Dec 2015 A1
20150347393 Futrell et al. Dec 2015 A1
20150347552 Habouzit et al. Dec 2015 A1
20150347733 Tsou et al. Dec 2015 A1
20150347985 Gross et al. Dec 2015 A1
20150348533 Saddler et al. Dec 2015 A1
20150348547 Paulik et al. Dec 2015 A1
20150348548 Piernot et al. Dec 2015 A1
20150348549 Giuli et al. Dec 2015 A1
20150348551 Gruber et al. Dec 2015 A1
20150348554 Orr et al. Dec 2015 A1
20150348555 Sugita Dec 2015 A1
20150348565 Rhoten et al. Dec 2015 A1
20150349934 Pollack et al. Dec 2015 A1
20150350031 Burks et al. Dec 2015 A1
20150350147 Shepherd et al. Dec 2015 A1
20150350342 Thorpe et al. Dec 2015 A1
20150350594 Mate et al. Dec 2015 A1
20150352999 Bando et al. Dec 2015 A1
20150355879 Beckhardt et al. Dec 2015 A1
20150356410 Faith et al. Dec 2015 A1
20150363587 Ahn et al. Dec 2015 A1
20150364128 Zhao et al. Dec 2015 A1
20150364140 Thörn Dec 2015 A1
20150365251 Kinoshita et al. Dec 2015 A1
20150370455 Van Os et al. Dec 2015 A1
20150370531 Faaborg Dec 2015 A1
20150370780 Wang et al. Dec 2015 A1
20150370787 Akbacak et al. Dec 2015 A1
20150370884 Hurley et al. Dec 2015 A1
20150371215 Zhou et al. Dec 2015 A1
20150371529 Dolecki Dec 2015 A1
20150371639 Foerster et al. Dec 2015 A1
20150371663 Gustafson et al. Dec 2015 A1
20150371664 Bar-Or et al. Dec 2015 A1
20150371665 Naik et al. Dec 2015 A1
20150373183 Woolsey et al. Dec 2015 A1
20150373428 Trollope et al. Dec 2015 A1
20150379118 Wickenkamp et al. Dec 2015 A1
20150379414 Yeh et al. Dec 2015 A1
20150379993 Subhojit et al. Dec 2015 A1
20150381923 Wickenkamp et al. Dec 2015 A1
20150382047 Van Os Dec 2015 A1
20150382079 Lister et al. Dec 2015 A1
20150382147 Clark et al. Dec 2015 A1
20150382322 Migicovsky et al. Dec 2015 A1
20160004499 Kim et al. Jan 2016 A1
20160004690 Bangalore et al. Jan 2016 A1
20160005320 deCharms et al. Jan 2016 A1
20160006795 Yunten Jan 2016 A1
20160012038 Edwards et al. Jan 2016 A1
20160014476 Caliendo, Jr. et al. Jan 2016 A1
20160018872 Tu et al. Jan 2016 A1
20160018899 Tu et al. Jan 2016 A1
20160018900 Tu et al. Jan 2016 A1
20160018959 Yamashita et al. Jan 2016 A1
20160019886 Hong Jan 2016 A1
20160019896 Alvarez Guevara et al. Jan 2016 A1
20160021414 Padi et al. Jan 2016 A1
20160026242 Burns et al. Jan 2016 A1
20160026258 Ou et al. Jan 2016 A1
20160027431 Kurzweil et al. Jan 2016 A1
20160028666 Li Jan 2016 A1
20160028802 Balasingh et al. Jan 2016 A1
20160029316 Mohan et al. Jan 2016 A1
20160034042 Joo Feb 2016 A1
20160034447 Shin Feb 2016 A1
20160034811 Paulik et al. Feb 2016 A1
20160036750 Yuan et al. Feb 2016 A1
20160036953 Lee et al. Feb 2016 A1
20160041809 Clayton et al. Feb 2016 A1
20160042735 Vibbert et al. Feb 2016 A1
20160042748 Jain et al. Feb 2016 A1
20160043905 Fiedler Feb 2016 A1
20160048666 Dey et al. Feb 2016 A1
20160050254 Rao et al. Feb 2016 A1
20160055422 Li Feb 2016 A1
20160057203 Gärdenfors et al. Feb 2016 A1
20160057475 Liu Feb 2016 A1
20160061623 Pahwa et al. Mar 2016 A1
20160062459 Publicover et al. Mar 2016 A1
20160062605 Agarwal et al. Mar 2016 A1
20160063094 Udupa et al. Mar 2016 A1
20160063095 Nassar et al. Mar 2016 A1
20160063998 Krishnamoorthy et al. Mar 2016 A1
20160065155 Bharj et al. Mar 2016 A1
20160065626 Jain et al. Mar 2016 A1
20160066020 Mountain Mar 2016 A1
20160066360 Vinegrad et al. Mar 2016 A1
20160070581 Soon-Shiong Mar 2016 A1
20160071516 Lee et al. Mar 2016 A1
20160071517 Beaver et al. Mar 2016 A1
20160071520 Hayakawa Mar 2016 A1
20160071521 Haughay Mar 2016 A1
20160072940 Cronin Mar 2016 A1
20160077794 Kim et al. Mar 2016 A1
20160078359 Csurka et al. Mar 2016 A1
20160078860 Paulik et al. Mar 2016 A1
20160080165 Ehsani et al. Mar 2016 A1
20160080475 Singh et al. Mar 2016 A1
20160085295 Shimy et al. Mar 2016 A1
20160085827 Chadha et al. Mar 2016 A1
20160086116 Rao et al. Mar 2016 A1
20160086599 Kurata et al. Mar 2016 A1
20160088335 Zucchetta Mar 2016 A1
20160091871 Marti et al. Mar 2016 A1
20160091967 Prokofieva et al. Mar 2016 A1
20160092046 Hong et al. Mar 2016 A1
20160092074 Raux et al. Mar 2016 A1
20160092434 Bellegarda Mar 2016 A1
20160092447 Pathurudeen et al. Mar 2016 A1
20160092766 Sainath et al. Mar 2016 A1
20160093291 Kim Mar 2016 A1
20160093298 Naik et al. Mar 2016 A1
20160093301 Bellegarda et al. Mar 2016 A1
20160093304 Kim et al. Mar 2016 A1
20160094700 Lee et al. Mar 2016 A1
20160094889 Venkataraman et al. Mar 2016 A1
20160094979 Naik et al. Mar 2016 A1
20160098991 Luo et al. Apr 2016 A1
20160098992 Renard et al. Apr 2016 A1
20160099892 Palakovich et al. Apr 2016 A1
20160099984 Karagiannis et al. Apr 2016 A1
20160104480 Sharifi Apr 2016 A1
20160104486 Penilla et al. Apr 2016 A1
20160105308 Dutt Apr 2016 A1
20160111091 Bakish Apr 2016 A1
20160112746 Zhang et al. Apr 2016 A1
20160112792 Lee et al. Apr 2016 A1
20160116980 George-Svahn et al. Apr 2016 A1
20160117386 Ajmera et al. Apr 2016 A1
20160118048 Heide Apr 2016 A1
20160119338 Cheyer Apr 2016 A1
20160125048 Hamada May 2016 A1
20160125071 Gabbai May 2016 A1
20160132046 Beoughter et al. May 2016 A1
20160132290 Raux May 2016 A1
20160132484 Nauze et al. May 2016 A1
20160132488 Clark et al. May 2016 A1
20160133254 Vogel et al. May 2016 A1
20160139662 Dabhade May 2016 A1
20160139720 Kritt et al. May 2016 A1
20160140951 Agiomyrgiannakis et al. May 2016 A1
20160140962 Sharifi May 2016 A1
20160147725 Patten et al. May 2016 A1
20160147739 Lim et al. May 2016 A1
20160148610 Kennewick, Jr. et al. May 2016 A1
20160148612 Guo et al. May 2016 A1
20160148613 Kwon et al. May 2016 A1
20160149966 Remash et al. May 2016 A1
20160150020 Farmer et al. May 2016 A1
20160151668 Barnes et al. Jun 2016 A1
20160154624 Son et al. Jun 2016 A1
20160154792 Sarikaya et al. Jun 2016 A1
20160154880 Hoarty Jun 2016 A1
20160155442 Kannan et al. Jun 2016 A1
20160155443 Khan et al. Jun 2016 A1
20160156574 Hum et al. Jun 2016 A1
20160156990 Miccoy et al. Jun 2016 A1
20160162456 Munro et al. Jun 2016 A1
20160163311 Crook et al. Jun 2016 A1
20160163312 Naik et al. Jun 2016 A1
20160169267 Pool Jun 2016 A1
20160170710 Kim et al. Jun 2016 A1
20160170966 Kolo Jun 2016 A1
20160171980 Liddell et al. Jun 2016 A1
20160173578 Sharma et al. Jun 2016 A1
20160173617 Allinson Jun 2016 A1
20160173929 Klappert Jun 2016 A1
20160173960 Snibbe et al. Jun 2016 A1
20160179462 Bjorkengren Jun 2016 A1
20160179464 Reddy et al. Jun 2016 A1
20160179787 Deleeuw Jun 2016 A1
20160180840 Siddiq et al. Jun 2016 A1
20160180844 Vanblon et al. Jun 2016 A1
20160182410 Janakiraman et al. Jun 2016 A1
20160182709 Kim et al. Jun 2016 A1
20160188181 Smith Jun 2016 A1
20160188738 Gruber et al. Jun 2016 A1
20160189198 Daniel et al. Jun 2016 A1
20160189715 Nishikawa Jun 2016 A1
20160189717 Kannan et al. Jun 2016 A1
20160196110 Yehoshua et al. Jul 2016 A1
20160198319 Huang et al. Jul 2016 A1
20160202957 Siddall et al. Jul 2016 A1
20160203002 Kannan et al. Jul 2016 A1
20160203193 Kevin et al. Jul 2016 A1
20160210551 Lee et al. Jul 2016 A1
20160210981 Lee Jul 2016 A1
20160212206 Wu et al. Jul 2016 A1
20160212208 Kulkarni et al. Jul 2016 A1
20160212488 Os et al. Jul 2016 A1
20160217784 Gelfenbeyn et al. Jul 2016 A1
20160217794 Imoto et al. Jul 2016 A1
20160224540 Stewart et al. Aug 2016 A1
20160224559 Hicks et al. Aug 2016 A1
20160224774 Pender Aug 2016 A1
20160225372 Cheung et al. Aug 2016 A1
20160226956 Hong et al. Aug 2016 A1
20160227107 Beaumont Aug 2016 A1
20160227633 Sun et al. Aug 2016 A1
20160232500 Wang et al. Aug 2016 A1
20160234206 Tunnell et al. Aug 2016 A1
20160239480 Larcheveque et al. Aug 2016 A1
20160239568 Packer et al. Aug 2016 A1
20160239645 Heo et al. Aug 2016 A1
20160239848 Chang et al. Aug 2016 A1
20160240187 Fleizach et al. Aug 2016 A1
20160240189 Lee et al. Aug 2016 A1
20160240192 Raghuvir Aug 2016 A1
20160242148 Reed Aug 2016 A1
20160247061 Trask et al. Aug 2016 A1
20160249319 Dotan-Cohen et al. Aug 2016 A1
20160253312 Rhodes Sep 2016 A1
20160253528 Gao et al. Sep 2016 A1
20160259623 Sumner et al. Sep 2016 A1
20160259656 Sumner et al. Sep 2016 A1
20160259779 Labský et al. Sep 2016 A1
20160260431 Newendorp et al. Sep 2016 A1
20160260433 Sumner et al. Sep 2016 A1
20160260434 Gelfenbeyn et al. Sep 2016 A1
20160260436 Lemay et al. Sep 2016 A1
20160262442 Davila et al. Sep 2016 A1
20160266871 Schmid et al. Sep 2016 A1
20160267904 Biadsy et al. Sep 2016 A1
20160269540 Butcher et al. Sep 2016 A1
20160274938 Strinati et al. Sep 2016 A1
20160275941 Bellegarda et al. Sep 2016 A1
20160275947 Li et al. Sep 2016 A1
20160282824 Smallwood et al. Sep 2016 A1
20160282956 Ouyang et al. Sep 2016 A1
20160283055 Haghighat et al. Sep 2016 A1
20160283185 Mclaren et al. Sep 2016 A1
20160284005 Daniel et al. Sep 2016 A1
20160284199 Dotan-Cohen et al. Sep 2016 A1
20160285808 Franklin et al. Sep 2016 A1
20160286045 Shaltiel et al. Sep 2016 A1
20160291831 Baek Oct 2016 A1
20160292603 Prajapati et al. Oct 2016 A1
20160293157 Chen et al. Oct 2016 A1
20160293167 Chen et al. Oct 2016 A1
20160293168 Chen Oct 2016 A1
20160294755 Prabhu Oct 2016 A1
20160294813 Zou Oct 2016 A1
20160299685 Zhai et al. Oct 2016 A1
20160299882 Hegerty et al. Oct 2016 A1
20160299883 Zhu et al. Oct 2016 A1
20160299977 Hreha Oct 2016 A1
20160300571 Foerster et al. Oct 2016 A1
20160301639 Liu et al. Oct 2016 A1
20160306683 Standley et al. Oct 2016 A1
20160307566 Bellegarda Oct 2016 A1
20160308799 Schubert et al. Oct 2016 A1
20160309035 Li Oct 2016 A1
20160313906 Kilchenko et al. Oct 2016 A1
20160314788 Jitkoff et al. Oct 2016 A1
20160314789 Marcheret et al. Oct 2016 A1
20160314792 Alvarez et al. Oct 2016 A1
20160315996 Ha et al. Oct 2016 A1
20160316349 Lee et al. Oct 2016 A1
20160317924 Tanaka et al. Nov 2016 A1
20160320838 Teller et al. Nov 2016 A1
20160321239 Iso-Sipilä et al. Nov 2016 A1
20160321243 Walia et al. Nov 2016 A1
20160321261 Spasojevic et al. Nov 2016 A1
20160321358 Kanani et al. Nov 2016 A1
20160322043 Bellegarda Nov 2016 A1
20160322044 Jung et al. Nov 2016 A1
20160322045 Hatfield et al. Nov 2016 A1
20160322048 Amano et al. Nov 2016 A1
20160322050 Wang et al. Nov 2016 A1
20160322055 Sainath et al. Nov 2016 A1
20160328134 Xu Nov 2016 A1
20160328147 Zhang et al. Nov 2016 A1
20160328205 Agrawal et al. Nov 2016 A1
20160328893 Cordova et al. Nov 2016 A1
20160329060 Ito et al. Nov 2016 A1
20160334973 Reckhow et al. Nov 2016 A1
20160335138 Surti et al. Nov 2016 A1
20160335139 Hurley et al. Nov 2016 A1
20160335532 Sanghavi et al. Nov 2016 A1
20160336007 Hanazawa et al. Nov 2016 A1
20160336010 Lindahl Nov 2016 A1
20160336011 Koll et al. Nov 2016 A1
20160336024 Choi et al. Nov 2016 A1
20160337299 Lane et al. Nov 2016 A1
20160337301 Rollins et al. Nov 2016 A1
20160342317 Lim et al. Nov 2016 A1
20160342685 Basu et al. Nov 2016 A1
20160342781 Jeon Nov 2016 A1
20160342803 Goodridge et al. Nov 2016 A1
20160350070 Sung et al. Dec 2016 A1
20160350650 Leeman-Munk et al. Dec 2016 A1
20160350812 Priness et al. Dec 2016 A1
20160351190 Piernot et al. Dec 2016 A1
20160352567 Robbins et al. Dec 2016 A1
20160352924 Senarath et al. Dec 2016 A1
20160357304 Hatori et al. Dec 2016 A1
20160357728 Bellegarda et al. Dec 2016 A1
20160357790 Elkington et al. Dec 2016 A1
20160357861 Carlhian et al. Dec 2016 A1
20160357870 Hentschel et al. Dec 2016 A1
20160358598 Williams et al. Dec 2016 A1
20160358600 Nallasamy et al. Dec 2016 A1
20160358603 Azam et al. Dec 2016 A1
20160358609 Connell et al. Dec 2016 A1
20160358619 Ramprashad et al. Dec 2016 A1
20160359771 Sridhar Dec 2016 A1
20160360039 Sanghavi et al. Dec 2016 A1
20160360336 Gross et al. Dec 2016 A1
20160360382 Gross et al. Dec 2016 A1
20160364378 Futrell et al. Dec 2016 A1
20160364382 Sarikaya Dec 2016 A1
20160365101 Foy et al. Dec 2016 A1
20160371054 Beaumont et al. Dec 2016 A1
20160371250 Rhodes Dec 2016 A1
20160372112 Miller et al. Dec 2016 A1
20160372119 Sak et al. Dec 2016 A1
20160378747 Orr et al. Dec 2016 A1
20160379091 Lin et al. Dec 2016 A1
20160379105 Moore, Jr. Dec 2016 A1
20160379626 Deisher et al. Dec 2016 A1
20160379632 Hoffmeister et al. Dec 2016 A1
20160379633 Lehman et al. Dec 2016 A1
20160379639 Weinstein et al. Dec 2016 A1
20160379641 Liu et al. Dec 2016 A1
20170000348 Karsten et al. Jan 2017 A1
20170003931 Dvortsov et al. Jan 2017 A1
20170004209 Johl et al. Jan 2017 A1
20170004409 Chu et al. Jan 2017 A1
20170004824 Yoo et al. Jan 2017 A1
20170005818 Gould Jan 2017 A1
20170006329 Jang et al. Jan 2017 A1
20170011091 Chehreghani Jan 2017 A1
20170011279 Soldevila et al. Jan 2017 A1
20170011303 Annapureddy et al. Jan 2017 A1
20170011742 Jing et al. Jan 2017 A1
20170013124 Havelka et al. Jan 2017 A1
20170013331 Watanabe et al. Jan 2017 A1
20170018271 Khan et al. Jan 2017 A1
20170019987 Dragone et al. Jan 2017 A1
20170023963 Davis et al. Jan 2017 A1
20170025124 Mixter et al. Jan 2017 A1
20170026318 Daniel et al. Jan 2017 A1
20170026509 Rand Jan 2017 A1
20170027522 Van Hasselt et al. Feb 2017 A1
20170031576 Saoji et al. Feb 2017 A1
20170031711 Wu et al. Feb 2017 A1
20170032440 Paton Feb 2017 A1
20170032783 Lord et al. Feb 2017 A1
20170032787 Dayal Feb 2017 A1
20170032791 Elson et al. Feb 2017 A1
20170034087 Borenstein et al. Feb 2017 A1
20170039283 Bennett et al. Feb 2017 A1
20170039475 Cheyer et al. Feb 2017 A1
20170040002 Basson et al. Feb 2017 A1
20170041388 Tal et al. Feb 2017 A1
20170046025 Dascola et al. Feb 2017 A1
20170046330 Si et al. Feb 2017 A1
20170047063 Ohmura et al. Feb 2017 A1
20170052760 Johnson et al. Feb 2017 A1
20170053652 Choi et al. Feb 2017 A1
20170055895 Jardins et al. Mar 2017 A1
20170060853 Lee et al. Mar 2017 A1
20170061423 Bryant et al. Mar 2017 A1
20170068423 Napolitano et al. Mar 2017 A1
20170068513 Stasior et al. Mar 2017 A1
20170068550 Zeitlin Mar 2017 A1
20170068670 Orr et al. Mar 2017 A1
20170069308 Aleksic et al. Mar 2017 A1
20170069321 Toiyama Mar 2017 A1
20170069327 Heigold et al. Mar 2017 A1
20170075653 Dawidowsky et al. Mar 2017 A1
20170076518 Patterson et al. Mar 2017 A1
20170076720 Gopalan et al. Mar 2017 A1
20170076721 Bargetzi et al. Mar 2017 A1
20170078490 Kaminsky et al. Mar 2017 A1
20170083179 Gruber et al. Mar 2017 A1
20170083285 Meyers et al. Mar 2017 A1
20170083504 Huang Mar 2017 A1
20170083506 Liu et al. Mar 2017 A1
20170084277 Sharifi Mar 2017 A1
20170085547 De Aguiar et al. Mar 2017 A1
20170085696 Abkairov Mar 2017 A1
20170090428 Oohara Mar 2017 A1
20170090569 Levesque Mar 2017 A1
20170090864 Jorgovanovic Mar 2017 A1
20170091168 Bellegarda et al. Mar 2017 A1
20170091169 Bellegarda et al. Mar 2017 A1
20170091612 Gruber et al. Mar 2017 A1
20170092259 Jeon Mar 2017 A1
20170092270 Newendorp et al. Mar 2017 A1
20170092278 Evermann et al. Mar 2017 A1
20170093356 Cudak et al. Mar 2017 A1
20170097743 Hameed et al. Apr 2017 A1
20170102837 Toumpelis Apr 2017 A1
20170102915 Kuscher et al. Apr 2017 A1
20170103749 Zhao et al. Apr 2017 A1
20170103752 Senior et al. Apr 2017 A1
20170105190 Logan et al. Apr 2017 A1
20170108236 Guan et al. Apr 2017 A1
20170110117 Chakladar et al. Apr 2017 A1
20170110125 Xu et al. Apr 2017 A1
20170116177 Walia Apr 2017 A1
20170116982 Gelfenbeyn et al. Apr 2017 A1
20170116987 Kang et al. Apr 2017 A1
20170116989 Yadgar et al. Apr 2017 A1
20170124190 Wang et al. May 2017 A1
20170124311 Li et al. May 2017 A1
20170124531 McCormack May 2017 A1
20170125016 Wang May 2017 A1
20170127124 Wilson et al. May 2017 A9
20170131778 Iyer May 2017 A1
20170132019 Karashchuk et al. May 2017 A1
20170132199 Vescovi et al. May 2017 A1
20170133007 Drewes May 2017 A1
20170133009 Cho et al. May 2017 A1
20170134807 Shaw et al. May 2017 A1
20170140041 Dotan-Cohen et al. May 2017 A1
20170140052 Bufe, III et al. May 2017 A1
20170140644 Hwang et al. May 2017 A1
20170140760 Sachdev May 2017 A1
20170147722 Greenwood May 2017 A1
20170147841 Stagg et al. May 2017 A1
20170148044 Fukuda et al. May 2017 A1
20170148307 Yeom et al. May 2017 A1
20170154033 Lee Jun 2017 A1
20170154055 Dimson et al. Jun 2017 A1
20170154628 Mohajer et al. Jun 2017 A1
20170155940 Jin et al. Jun 2017 A1
20170155965 Ward Jun 2017 A1
20170161018 Lemay et al. Jun 2017 A1
20170161268 Badaskar Jun 2017 A1
20170161293 Ionescu et al. Jun 2017 A1
20170161393 Oh et al. Jun 2017 A1
20170161439 Raduchel et al. Jun 2017 A1
20170161500 Yang Jun 2017 A1
20170162191 Grost et al. Jun 2017 A1
20170162202 Anthony et al. Jun 2017 A1
20170162203 Huang et al. Jun 2017 A1
20170169506 Wishne et al. Jun 2017 A1
20170169818 Vanblon et al. Jun 2017 A1
20170169819 Mese et al. Jun 2017 A1
20170171139 Marra et al. Jun 2017 A1
20170171387 Vendrow Jun 2017 A1
20170177080 Deleeuw Jun 2017 A1
20170177547 Ciereszko et al. Jun 2017 A1
20170178619 Naik et al. Jun 2017 A1
20170178620 Fleizach et al. Jun 2017 A1
20170178626 Gruber et al. Jun 2017 A1
20170178666 Yu Jun 2017 A1
20170180499 Gelfenbeyn et al. Jun 2017 A1
20170185375 Martel et al. Jun 2017 A1
20170185581 Boja et al. Jun 2017 A1
20170186429 Giuli et al. Jun 2017 A1
20170186446 Wosk et al. Jun 2017 A1
20170187711 Joo et al. Jun 2017 A1
20170193083 Bhatt et al. Jul 2017 A1
20170195493 Sudarsan et al. Jul 2017 A1
20170195495 Deora et al. Jul 2017 A1
20170195636 Child et al. Jul 2017 A1
20170195856 Snyder et al. Jul 2017 A1
20170199870 Zheng et al. Jul 2017 A1
20170199874 Patel et al. Jul 2017 A1
20170200066 Wang et al. Jul 2017 A1
20170201609 Salmenkaita et al. Jul 2017 A1
20170201613 Engelke et al. Jul 2017 A1
20170201846 Katayama et al. Jul 2017 A1
20170206002 Badger et al. Jul 2017 A1
20170206899 Bryant et al. Jul 2017 A1
20170215052 Koum et al. Jul 2017 A1
20170220212 Yang et al. Aug 2017 A1
20170221486 Kurata et al. Aug 2017 A1
20170222961 Beach et al. Aug 2017 A1
20170223189 Meredith et al. Aug 2017 A1
20170227935 Su et al. Aug 2017 A1
20170228367 Pasupalak et al. Aug 2017 A1
20170228382 Haviv et al. Aug 2017 A1
20170229121 Taki et al. Aug 2017 A1
20170230429 Garmark et al. Aug 2017 A1
20170230497 Kim et al. Aug 2017 A1
20170230709 Van Os et al. Aug 2017 A1
20170235361 Rigazio et al. Aug 2017 A1
20170235618 Lin et al. Aug 2017 A1
20170235721 Almosallam et al. Aug 2017 A1
20170236512 Williams et al. Aug 2017 A1
20170236514 Nelson Aug 2017 A1
20170236517 Yu et al. Aug 2017 A1
20170238039 Sabattini Aug 2017 A1
20170242478 Ma Aug 2017 A1
20170242653 Lang et al. Aug 2017 A1
20170242657 Jarvis et al. Aug 2017 A1
20170242840 Lu et al. Aug 2017 A1
20170243468 Dotan-Cohen et al. Aug 2017 A1
20170243576 Millington et al. Aug 2017 A1
20170243583 Raichelgauz et al. Aug 2017 A1
20170243586 Civelli et al. Aug 2017 A1
20170249291 Patel Aug 2017 A1
20170249309 Sarikaya Aug 2017 A1
20170256256 Wang et al. Sep 2017 A1
20170257723 Morishita et al. Sep 2017 A1
20170262051 Tall et al. Sep 2017 A1
20170262432 Sarikaya et al. Sep 2017 A1
20170263247 Kang et al. Sep 2017 A1
20170263248 Gruber et al. Sep 2017 A1
20170263249 Akbacak et al. Sep 2017 A1
20170263254 Dewan et al. Sep 2017 A1
20170264451 Yu et al. Sep 2017 A1
20170264711 Natarajan et al. Sep 2017 A1
20170270092 He et al. Sep 2017 A1
20170270715 Lindsay et al. Sep 2017 A1
20170270822 Cohen Sep 2017 A1
20170270912 Levit et al. Sep 2017 A1
20170273044 Alsina Sep 2017 A1
20170277691 Agarwal Sep 2017 A1
20170278513 Li et al. Sep 2017 A1
20170278514 Mathias et al. Sep 2017 A1
20170285915 Napolitano et al. Oct 2017 A1
20170286397 Gonzalez Oct 2017 A1
20170286407 Chochowski et al. Oct 2017 A1
20170287218 Nuernberger et al. Oct 2017 A1
20170287472 Ogawa et al. Oct 2017 A1
20170289305 Liensberger et al. Oct 2017 A1
20170295446 Shivappa Oct 2017 A1
20170301348 Chen et al. Oct 2017 A1
20170308552 Soni et al. Oct 2017 A1
20170308589 Liu et al. Oct 2017 A1
20170308609 Berkhin et al. Oct 2017 A1
20170311005 Lin Oct 2017 A1
20170316775 Le et al. Nov 2017 A1
20170316779 Mohapatra et al. Nov 2017 A1
20170316782 Haughay Nov 2017 A1
20170319123 Voss et al. Nov 2017 A1
20170323637 Naik Nov 2017 A1
20170329466 Krenkler et al. Nov 2017 A1
20170329490 Esinovskaya et al. Nov 2017 A1
20170329572 Shah et al. Nov 2017 A1
20170329630 Jann et al. Nov 2017 A1
20170330567 Van Wissen et al. Nov 2017 A1
20170336920 Chan et al. Nov 2017 A1
20170337035 Choudhary et al. Nov 2017 A1
20170337478 Sarikaya et al. Nov 2017 A1
20170337540 Buckman et al. Nov 2017 A1
20170345411 Raitio et al. Nov 2017 A1
20170345420 Barnett, Jr. Nov 2017 A1
20170345429 Hardee et al. Nov 2017 A1
20170346949 Sanghavi et al. Nov 2017 A1
20170347180 Petrank Nov 2017 A1
20170347222 Kanter Nov 2017 A1
20170351487 Avilés-Casco et al. Dec 2017 A1
20170352346 Paulik et al. Dec 2017 A1
20170352350 Booker et al. Dec 2017 A1
20170357478 Piersol et al. Dec 2017 A1
20170357529 Venkatraman et al. Dec 2017 A1
20170357632 Pagallo et al. Dec 2017 A1
20170357633 Wang et al. Dec 2017 A1
20170357637 Nell et al. Dec 2017 A1
20170357640 Bellegarda et al. Dec 2017 A1
20170357716 Bellegarda et al. Dec 2017 A1
20170358300 Laurens et al. Dec 2017 A1
20170358301 Raitio et al. Dec 2017 A1
20170358302 Orr et al. Dec 2017 A1
20170358303 Walker et al. Dec 2017 A1
20170358304 Castillo et al. Dec 2017 A1
20170358305 Kudurshian et al. Dec 2017 A1
20170358317 James Dec 2017 A1
20170359680 Ledvina et al. Dec 2017 A1
20170365251 Park et al. Dec 2017 A1
20170371509 Jung et al. Dec 2017 A1
20170371865 Eck et al. Dec 2017 A1
20170371866 Eck Dec 2017 A1
20170371885 Aggarwal et al. Dec 2017 A1
20170372703 Sung et al. Dec 2017 A1
20170372719 Li et al. Dec 2017 A1
20170374093 Dhar et al. Dec 2017 A1
20170374176 Agrawal et al. Dec 2017 A1
20180004372 Zurek et al. Jan 2018 A1
20180004396 Ying Jan 2018 A1
20180005112 Iso-Sipila et al. Jan 2018 A1
20180007060 Leblang et al. Jan 2018 A1
20180007096 Levin et al. Jan 2018 A1
20180007210 Todasco Jan 2018 A1
20180007538 Naik et al. Jan 2018 A1
20180012596 Piernot et al. Jan 2018 A1
20180018248 Bhargava et al. Jan 2018 A1
20180018590 Szeto et al. Jan 2018 A1
20180018814 Patrik et al. Jan 2018 A1
20180018959 Des Jardins et al. Jan 2018 A1
20180018973 Moreno et al. Jan 2018 A1
20180020093 Bentitou et al. Jan 2018 A1
20180024985 Asano Jan 2018 A1
20180025124 Mohr et al. Jan 2018 A1
20180025287 Mathew et al. Jan 2018 A1
20180028918 Tang et al. Feb 2018 A1
20180033431 Newendorp et al. Feb 2018 A1
20180033435 Jacobs, II Feb 2018 A1
20180033436 Zhou Feb 2018 A1
20180039239 Burchard Feb 2018 A1
20180041571 Rogers et al. Feb 2018 A1
20180045963 Hoover et al. Feb 2018 A1
20180046340 Mall Feb 2018 A1
20180046851 Kienzle et al. Feb 2018 A1
20180047201 Filev et al. Feb 2018 A1
20180047288 Cordell et al. Feb 2018 A1
20180047391 Baik et al. Feb 2018 A1
20180047393 Tian et al. Feb 2018 A1
20180047406 Park Feb 2018 A1
20180052909 Sharifi et al. Feb 2018 A1
20180054505 Hart et al. Feb 2018 A1
20180060032 Boesen Mar 2018 A1
20180060301 Li et al. Mar 2018 A1
20180060312 Won Mar 2018 A1
20180060555 Boesen Mar 2018 A1
20180061400 Carbune et al. Mar 2018 A1
20180061401 Sarikaya et al. Mar 2018 A1
20180062691 Barnett, Jr. Mar 2018 A1
20180063276 Foged Mar 2018 A1
20180063308 Crystal et al. Mar 2018 A1
20180063324 Van Meter, II Mar 2018 A1
20180063624 Boesen Mar 2018 A1
20180067904 Li Mar 2018 A1
20180067914 Chen et al. Mar 2018 A1
20180067918 Bellegarda et al. Mar 2018 A1
20180067929 Ahn Mar 2018 A1
20180068074 Shen Mar 2018 A1
20180068194 Matsuda Mar 2018 A1
20180069743 Bakken et al. Mar 2018 A1
20180075659 Browy et al. Mar 2018 A1
20180075847 Lee et al. Mar 2018 A1
20180075849 Khoury et al. Mar 2018 A1
20180077095 Deyle et al. Mar 2018 A1
20180077648 Nguyen Mar 2018 A1
20180081739 Gravenites et al. Mar 2018 A1
20180082692 Khoury et al. Mar 2018 A1
20180083898 Pham Mar 2018 A1
20180088788 Cheung et al. Mar 2018 A1
20180088902 Mese et al. Mar 2018 A1
20180088969 Vanblon et al. Mar 2018 A1
20180089166 Meyer et al. Mar 2018 A1
20180089588 Ravi et al. Mar 2018 A1
20180090143 Saddler et al. Mar 2018 A1
20180091604 Yamashita et al. Mar 2018 A1
20180091732 Wilson et al. Mar 2018 A1
20180091847 Wu et al. Mar 2018 A1
20180096683 James et al. Apr 2018 A1
20180096690 Mixter et al. Apr 2018 A1
20180097812 Gillett et al. Apr 2018 A1
20180101599 Kenneth et al. Apr 2018 A1
20180101925 Brinig et al. Apr 2018 A1
20180102914 Kawachi et al. Apr 2018 A1
20180103209 Fischler et al. Apr 2018 A1
20180107917 Hewavitharana et al. Apr 2018 A1
20180107945 Gao et al. Apr 2018 A1
20180108346 Paulik et al. Apr 2018 A1
20180108351 Beckhardt et al. Apr 2018 A1
20180108357 Liu Apr 2018 A1
20180109920 Aggarwal et al. Apr 2018 A1
20180113673 Sheynblat Apr 2018 A1
20180114591 Pribanic et al. Apr 2018 A1
20180121430 Kagoshima et al. May 2018 A1
20180121432 Parson et al. May 2018 A1
20180122376 Kojima May 2018 A1
20180122378 Mixter et al. May 2018 A1
20180126260 Chansoriya et al. May 2018 A1
20180129967 Herreshoff May 2018 A1
20180130470 Lemay et al. May 2018 A1
20180130471 Trufinescu et al. May 2018 A1
20180137097 Lim et al. May 2018 A1
20180137404 Fauceglia et al. May 2018 A1
20180137856 Gilbert May 2018 A1
20180137857 Zhou et al. May 2018 A1
20180137865 Ling May 2018 A1
20180143857 Anbazhagan et al. May 2018 A1
20180143967 Anbazhagan et al. May 2018 A1
20180144465 Hsieh et al. May 2018 A1
20180144615 Kinney et al. May 2018 A1
20180144746 Mishra et al. May 2018 A1
20180144748 Leong May 2018 A1
20180146089 Rauenbuehler et al. May 2018 A1
20180150744 Orr et al. May 2018 A1
20180152557 White et al. May 2018 A1
20180152558 Chan et al. May 2018 A1
20180152803 Seefeldt et al. May 2018 A1
20180157372 Kurabayashi Jun 2018 A1
20180157398 Kaehler et al. Jun 2018 A1
20180157408 Yu et al. Jun 2018 A1
20180157992 Susskind et al. Jun 2018 A1
20180158548 Taheri et al. Jun 2018 A1
20180158552 Liu et al. Jun 2018 A1
20180165278 He et al. Jun 2018 A1
20180165801 Kim et al. Jun 2018 A1
20180165857 Lee et al. Jun 2018 A1
20180166076 Higuchi et al. Jun 2018 A1
20180167884 Dawid et al. Jun 2018 A1
20180173403 Carbune et al. Jun 2018 A1
20180173542 Chan et al. Jun 2018 A1
20180174406 Arashi et al. Jun 2018 A1
20180174576 Soltau et al. Jun 2018 A1
20180174597 Lee et al. Jun 2018 A1
20180181370 Parkinson Jun 2018 A1
20180182376 Gysel et al. Jun 2018 A1
20180188840 Tamura et al. Jul 2018 A1
20180188948 Ouyang et al. Jul 2018 A1
20180189267 Takiel Jul 2018 A1
20180190263 Calef, III Jul 2018 A1
20180190273 Karimli et al. Jul 2018 A1
20180190279 Anderson et al. Jul 2018 A1
20180191670 Suyama Jul 2018 A1
20180196683 Radebaugh et al. Jul 2018 A1
20180205983 Lee et al. Jul 2018 A1
20180210874 Fuxman et al. Jul 2018 A1
20180213448 Segal et al. Jul 2018 A1
20180214061 Knoth et al. Aug 2018 A1
20180217810 Agrawal Aug 2018 A1
20180218735 Hunt et al. Aug 2018 A1
20180221783 Gamero Aug 2018 A1
20180225131 Tommy et al. Aug 2018 A1
20180225274 Tommy et al. Aug 2018 A1
20180232203 Gelfenbeyn et al. Aug 2018 A1
20180232608 Pradeep et al. Aug 2018 A1
20180232688 Pike et al. Aug 2018 A1
20180233132 Herold et al. Aug 2018 A1
20180233140 Koishida et al. Aug 2018 A1
20180247065 Rhee et al. Aug 2018 A1
20180253209 Jaygarl et al. Sep 2018 A1
20180253652 Palzer et al. Sep 2018 A1
20180260680 Finkelstein et al. Sep 2018 A1
20180267952 Osborne et al. Sep 2018 A1
20180268023 Korpusik et al. Sep 2018 A1
20180268106 Velaga Sep 2018 A1
20180268337 Miller et al. Sep 2018 A1
20180270343 Rout et al. Sep 2018 A1
20180275839 Kocienda et al. Sep 2018 A1
20180276197 Nell et al. Sep 2018 A1
20180277113 Hartung et al. Sep 2018 A1
20180278740 Choi et al. Sep 2018 A1
20180285056 Cutler et al. Oct 2018 A1
20180293086 Laird-Mcconnell et al. Oct 2018 A1
20180293984 Lindahl Oct 2018 A1
20180293988 Huang et al. Oct 2018 A1
20180293989 De et al. Oct 2018 A1
20180299878 Cella et al. Oct 2018 A1
20180300317 Bradbury Oct 2018 A1
20180300400 Paulus Oct 2018 A1
20180300608 Sevrens et al. Oct 2018 A1
20180300952 Evans et al. Oct 2018 A1
20180307216 Ypma et al. Oct 2018 A1
20180307603 Che Oct 2018 A1
20180308470 Park et al. Oct 2018 A1
20180308477 Nagasaka Oct 2018 A1
20180308480 Jang et al. Oct 2018 A1
20180308485 Kudurshian et al. Oct 2018 A1
20180308486 Saddler et al. Oct 2018 A1
20180308491 Oktem et al. Oct 2018 A1
20180314362 Kim et al. Nov 2018 A1
20180314552 Kim et al. Nov 2018 A1
20180314689 Wang et al. Nov 2018 A1
20180314981 Chen Nov 2018 A1
20180315415 Mosley et al. Nov 2018 A1
20180315416 Berthelsen et al. Nov 2018 A1
20180322112 Bellegarda et al. Nov 2018 A1
20180322881 Min et al. Nov 2018 A1
20180324518 Dusan et al. Nov 2018 A1
20180329508 Klein et al. Nov 2018 A1
20180329512 Liao et al. Nov 2018 A1
20180329677 Gruber et al. Nov 2018 A1
20180329957 Frazzingaro et al. Nov 2018 A1
20180329982 Patel et al. Nov 2018 A1
20180329998 Thomson et al. Nov 2018 A1
20180330714 Paulik et al. Nov 2018 A1
20180330721 Thomson et al. Nov 2018 A1
20180330722 Newendorp et al. Nov 2018 A1
20180330723 Acero et al. Nov 2018 A1
20180330729 Golipour et al. Nov 2018 A1
20180330730 Garg et al. Nov 2018 A1
20180330731 Zeitlin et al. Nov 2018 A1
20180330733 Orr et al. Nov 2018 A1
20180330737 Paulik et al. Nov 2018 A1
20180332118 Phipps et al. Nov 2018 A1
20180332389 Ekkizogloy et al. Nov 2018 A1
20180335903 Coffman et al. Nov 2018 A1
20180336006 Chakraborty et al. Nov 2018 A1
20180336049 Mukherjee et al. Nov 2018 A1
20180336184 Bellegarda et al. Nov 2018 A1
20180336197 Skilling et al. Nov 2018 A1
20180336275 Graham et al. Nov 2018 A1
20180336439 Kliger et al. Nov 2018 A1
20180336449 Adan et al. Nov 2018 A1
20180336880 Arik et al. Nov 2018 A1
20180336885 Mukherjee et al. Nov 2018 A1
20180336892 Kim et al. Nov 2018 A1
20180336893 Robinson et al. Nov 2018 A1
20180336894 Graham et al. Nov 2018 A1
20180336904 Piercy et al. Nov 2018 A1
20180336905 Kim et al. Nov 2018 A1
20180336911 Dahl et al. Nov 2018 A1
20180336920 Bastian et al. Nov 2018 A1
20180338191 Van Scheltinga et al. Nov 2018 A1
20180341643 Alders et al. Nov 2018 A1
20180342243 Vanblon et al. Nov 2018 A1
20180343557 Naik et al. Nov 2018 A1
20180349084 Nagasaka et al. Dec 2018 A1
20180349346 Hatori et al. Dec 2018 A1
20180349349 Bellegarda et al. Dec 2018 A1
20180349447 Maccartney et al. Dec 2018 A1
20180349472 Kohlschuetter et al. Dec 2018 A1
20180349728 Wang et al. Dec 2018 A1
20180350345 Naik Dec 2018 A1
20180350353 Gruber et al. Dec 2018 A1
20180357073 Johnson et al. Dec 2018 A1
20180357308 Cheyer Dec 2018 A1
20180358015 Cash et al. Dec 2018 A1
20180358019 Mont-Reynaud Dec 2018 A1
20180365653 Cleaver et al. Dec 2018 A1
20180366105 Kim Dec 2018 A1
20180366110 Hashem et al. Dec 2018 A1
20180366116 Nicholson et al. Dec 2018 A1
20180373487 Gruber et al. Dec 2018 A1
20180373493 Watson et al. Dec 2018 A1
20180373796 Rathod Dec 2018 A1
20180374484 Huang et al. Dec 2018 A1
20190005024 Somech et al. Jan 2019 A1
20190012141 Piersol et al. Jan 2019 A1
20190012445 Lesso et al. Jan 2019 A1
20190012449 Cheyer Jan 2019 A1
20190012599 El Kaliouby et al. Jan 2019 A1
20190013018 Rekstad Jan 2019 A1
20190013025 Alcorn et al. Jan 2019 A1
20190014450 Gruber et al. Jan 2019 A1
20190019077 Griffin et al. Jan 2019 A1
20190019508 Rochford et al. Jan 2019 A1
20190020482 Gupta et al. Jan 2019 A1
20190027152 Huang et al. Jan 2019 A1
20190034040 Shah et al. Jan 2019 A1
20190034826 Ahmad et al. Jan 2019 A1
20190035385 Lawson et al. Jan 2019 A1
20190035405 Haughay Jan 2019 A1
20190037258 Justin et al. Jan 2019 A1
20190042059 Baer Feb 2019 A1
20190042627 Osotio et al. Feb 2019 A1
20190043507 Huang et al. Feb 2019 A1
20190044854 Yang et al. Feb 2019 A1
20190045040 Lee et al. Feb 2019 A1
20190051306 Torama et al. Feb 2019 A1
20190051309 Kim et al. Feb 2019 A1
20190057697 Giuli et al. Feb 2019 A1
20190065144 Sumner et al. Feb 2019 A1
20190065993 Srinivasan et al. Feb 2019 A1
20190066674 Jaygarl et al. Feb 2019 A1
20190068810 Okamoto et al. Feb 2019 A1
20190173996 Butcher et al. Feb 2019 A1
20190073607 Jia et al. Mar 2019 A1
20190073998 Leblang et al. Mar 2019 A1
20190074009 Kim et al. Mar 2019 A1
20190074015 Orr et al. Mar 2019 A1
20190074016 Orr et al. Mar 2019 A1
20190079476 Funes Mar 2019 A1
20190079724 Feuz et al. Mar 2019 A1
20190080685 Johnson, Jr. Mar 2019 A1
20190080698 Miller Mar 2019 A1
20190082044 Olivia et al. Mar 2019 A1
20190087205 Guday Mar 2019 A1
20190087412 Seyed Ibrahim et al. Mar 2019 A1
20190087455 He et al. Mar 2019 A1
20190090812 Martin et al. Mar 2019 A1
20190095050 Gruber et al. Mar 2019 A1
20190095069 Proctor et al. Mar 2019 A1
20190095171 Carson et al. Mar 2019 A1
20190096134 Amacker et al. Mar 2019 A1
20190102145 Wilberding et al. Apr 2019 A1
20190102378 Piernot et al. Apr 2019 A1
20190102381 Futrell et al. Apr 2019 A1
20190103103 Ni et al. Apr 2019 A1
20190103112 Walker et al. Apr 2019 A1
20190108834 Nelson et al. Apr 2019 A1
20190114320 Patwardhan et al. Apr 2019 A1
20190116264 Sanghavi et al. Apr 2019 A1
20190122666 Raitio et al. Apr 2019 A1
20190122692 Binder et al. Apr 2019 A1
20190124019 Leon et al. Apr 2019 A1
20190129499 Li May 2019 A1
20190129615 Sundar et al. May 2019 A1
20190132694 Hanes et al. May 2019 A1
20190134501 Feder et al. May 2019 A1
20190138704 Shrivastava et al. May 2019 A1
20190139058 Clark et al. May 2019 A1
20190139541 Andersen et al. May 2019 A1
20190139563 Chen et al. May 2019 A1
20190141494 Gross et al. May 2019 A1
20190147052 Lu et al. May 2019 A1
20190147369 Gupta et al. May 2019 A1
20190147880 Booker et al. May 2019 A1
20190147883 Mellenthin et al. May 2019 A1
20190149972 Parks et al. May 2019 A1
20190156830 Devaraj et al. May 2019 A1
20190158994 Gross et al. May 2019 A1
20190163667 Feuz et al. May 2019 A1
20190164546 Piernot et al. May 2019 A1
20190172243 Mishra et al. Jun 2019 A1
20190172458 Mishra et al. Jun 2019 A1
20190172465 Lee et al. Jun 2019 A1
20190172467 Kim et al. Jun 2019 A1
20190179607 Thangarathnam et al. Jun 2019 A1
20190179890 Evermann Jun 2019 A1
20190180749 Carey et al. Jun 2019 A1
20190180750 Renard et al. Jun 2019 A1
20190180770 Kothari et al. Jun 2019 A1
20190182176 Niewczas Jun 2019 A1
20190187787 White et al. Jun 2019 A1
20190188326 Daianu et al. Jun 2019 A1
20190188328 Oyenan et al. Jun 2019 A1
20190189118 Piernot et al. Jun 2019 A1
20190189125 Van Os et al. Jun 2019 A1
20190190898 Cui Jun 2019 A1
20190197053 Graham et al. Jun 2019 A1
20190197119 Zhang et al. Jun 2019 A1
20190213498 Adjaoute Jul 2019 A1
20190213601 Hackman et al. Jul 2019 A1
20190213774 Jiao et al. Jul 2019 A1
20190213999 Grupen et al. Jul 2019 A1
20190214024 Gruber et al. Jul 2019 A1
20190220245 Martel et al. Jul 2019 A1
20190220246 Orr et al. Jul 2019 A1
20190220247 Lemay et al. Jul 2019 A1
20190220704 Schulz-Trieglaff et al. Jul 2019 A1
20190220727 Dohrmann et al. Jul 2019 A1
20190222684 Li et al. Jul 2019 A1
20190224049 Creasy et al. Jul 2019 A1
20190228581 Dascola et al. Jul 2019 A1
20190230215 Zhu et al. Jul 2019 A1
20190230426 Chun Jul 2019 A1
20190236130 Li et al. Aug 2019 A1
20190236459 Cheyer et al. Aug 2019 A1
20190237061 Rusak et al. Aug 2019 A1
20190243902 Saeki et al. Aug 2019 A1
20190244618 Newendorp et al. Aug 2019 A1
20190251167 Krishnapura Subbaraya et al. Aug 2019 A1
20190251339 Hawker Aug 2019 A1
20190251960 Maker et al. Aug 2019 A1
20190258852 Shimauchi et al. Aug 2019 A1
20190259386 Kudurshian et al. Aug 2019 A1
20190265886 Moon et al. Aug 2019 A1
20190266246 Wang et al. Aug 2019 A1
20190272318 Suzuki et al. Sep 2019 A1
20190272818 Fernandez et al. Sep 2019 A1
20190272825 O'Malley et al. Sep 2019 A1
20190272831 Kajarekar Sep 2019 A1
20190273963 Jobanputra et al. Sep 2019 A1
20190278841 Pusateri et al. Sep 2019 A1
20190279622 Liu et al. Sep 2019 A1
20190281387 Woo et al. Sep 2019 A1
20190287012 Asli et al. Sep 2019 A1
20190287522 Lambourne et al. Sep 2019 A1
20190294769 Lesso Sep 2019 A1
20190294962 Vezer et al. Sep 2019 A1
20190295529 Tomita Sep 2019 A1
20190295540 Grima Sep 2019 A1
20190295544 Garcia et al. Sep 2019 A1
20190303442 Peitz et al. Oct 2019 A1
20190303504 Pasumarthy Oct 2019 A1
20190304438 Qian et al. Oct 2019 A1
20190310765 Napolitano et al. Oct 2019 A1
20190311031 Powell et al. Oct 2019 A1
20190311708 Bengio et al. Oct 2019 A1
20190311720 Pasko Oct 2019 A1
20190318722 Bromand Oct 2019 A1
20190318724 Chao et al. Oct 2019 A1
20190318725 Le Roux et al. Oct 2019 A1
20190318732 Huang et al. Oct 2019 A1
20190318735 Chao et al. Oct 2019 A1
20190318739 Garg et al. Oct 2019 A1
20190324780 Zhu et al. Oct 2019 A1
20190324925 Toyoda et al. Oct 2019 A1
20190325081 Liu et al. Oct 2019 A1
20190325866 Bromand et al. Oct 2019 A1
20190333523 Kim et al. Oct 2019 A1
20190335567 Boudreau et al. Oct 2019 A1
20190339784 Lemay et al. Nov 2019 A1
20190340252 Huyghe Nov 2019 A1
20190341027 Vescovi et al. Nov 2019 A1
20190341056 Paulik et al. Nov 2019 A1
20190342748 Kwatra et al. Nov 2019 A1
20190347063 Liu et al. Nov 2019 A1
20190347525 Liem et al. Nov 2019 A1
20190348022 Park et al. Nov 2019 A1
20190349333 Pickover et al. Nov 2019 A1
20190349622 Kim et al. Nov 2019 A1
20190354256 Karunamuni et al. Nov 2019 A1
20190354548 Orr et al. Nov 2019 A1
20190355346 Bellegarda Nov 2019 A1
20190355384 Sereshki et al. Nov 2019 A1
20190361729 Gruber et al. Nov 2019 A1
20190361978 Ray et al. Nov 2019 A1
20190362252 Miller et al. Nov 2019 A1
20190362557 Lacey et al. Nov 2019 A1
20190369748 Hindi et al. Dec 2019 A1
20190369842 Dolbakian et al. Dec 2019 A1
20190369868 Jin et al. Dec 2019 A1
20190370292 Irani et al. Dec 2019 A1
20190370323 Davidson et al. Dec 2019 A1
20190370443 Lesso Dec 2019 A1
20190371315 Newendorp et al. Dec 2019 A1
20190371316 Weinstein et al. Dec 2019 A1
20190371317 Irani et al. Dec 2019 A1
20190371331 Schramm et al. Dec 2019 A1
20190372902 Piersol Dec 2019 A1
20190373102 Weinstein et al. Dec 2019 A1
20190377955 Swaminathan et al. Dec 2019 A1
20190385043 Choudhary et al. Dec 2019 A1
20190385418 Mixter et al. Dec 2019 A1
20190387352 Jot et al. Dec 2019 A1
20190391726 Iskandar et al. Dec 2019 A1
20200012718 Kung et al. Jan 2020 A1
20200019609 Yu et al. Jan 2020 A1
20200020326 Srinivasan et al. Jan 2020 A1
20200034421 Ferrucci et al. Jan 2020 A1
20200035224 Ward et al. Jan 2020 A1
20200042334 Radebaugh et al. Feb 2020 A1
20200043467 Qian et al. Feb 2020 A1
20200043471 Ma et al. Feb 2020 A1
20200043482 Lisa Feb 2020 A1
20200043489 Bradley et al. Feb 2020 A1
20200044485 Smith et al. Feb 2020 A1
20200045164 Kwatra et al. Feb 2020 A1
20200051554 Kim et al. Feb 2020 A1
20200051565 Singh Feb 2020 A1
20200051583 Wu et al. Feb 2020 A1
20200053218 Gray Feb 2020 A1
20200058299 Lee et al. Feb 2020 A1
20200065601 Andreassen Feb 2020 A1
20200066236 Giusti et al. Feb 2020 A1
20200073629 Lee et al. Mar 2020 A1
20200075018 Chen Mar 2020 A1
20200075040 Provost et al. Mar 2020 A1
20200076538 Soultan et al. Mar 2020 A1
20200081615 Yi et al. Mar 2020 A1
20200082807 Kim et al. Mar 2020 A1
20200084572 Jadav et al. Mar 2020 A1
20200090393 Shin et al. Mar 2020 A1
20200090658 Shin et al. Mar 2020 A1
20200091958 Curtis et al. Mar 2020 A1
20200092625 Raffle Mar 2020 A1
20200098352 Feinstein et al. Mar 2020 A1
20200098362 Piernot et al. Mar 2020 A1
20200098368 Lemay et al. Mar 2020 A1
20200103963 Kelly et al. Apr 2020 A1
20200104357 Bellegarda et al. Apr 2020 A1
20200104362 Yang et al. Apr 2020 A1
20200104369 Bellegarda Apr 2020 A1
20200104668 Sanghavi et al. Apr 2020 A1
20200105260 Piernot et al. Apr 2020 A1
20200112454 Brown et al. Apr 2020 A1
20200117717 Ramamurti et al. Apr 2020 A1
20200118566 Zhou Apr 2020 A1
20200118568 Kudurshian et al. Apr 2020 A1
20200125820 Kim et al. Apr 2020 A1
20200127988 Bradley et al. Apr 2020 A1
20200134316 Krishnamurthy et al. Apr 2020 A1
20200135180 Mukherjee et al. Apr 2020 A1
20200135209 Delfarah et al. Apr 2020 A1
20200135213 Kim et al. Apr 2020 A1
20200135226 Mittal et al. Apr 2020 A1
20200137230 Spohrer Apr 2020 A1
20200142505 Choi et al. May 2020 A1
20200142554 Lin et al. May 2020 A1
20200143812 Walker, II et al. May 2020 A1
20200143819 Delcroix et al. May 2020 A1
20200152186 Koh et al. May 2020 A1
20200159579 Shear et al. May 2020 A1
20200159651 Myers May 2020 A1
20200159801 Sekine May 2020 A1
20200160179 Chien et al. May 2020 A1
20200160838 Lee May 2020 A1
20200168120 Rodriguez Bravo May 2020 A1
20200169637 Sanghavi et al. May 2020 A1
20200175566 Bender et al. Jun 2020 A1
20200176004 Kleijn et al. Jun 2020 A1
20200176018 Feinauer et al. Jun 2020 A1
20200184057 Mukund Jun 2020 A1
20200184964 Myers et al. Jun 2020 A1
20200184966 Yavagal Jun 2020 A1
20200193997 Piernot et al. Jun 2020 A1
20200210142 Mu et al. Jul 2020 A1
20200211566 Kang et al. Jul 2020 A1
20200218074 Hoover et al. Jul 2020 A1
20200218780 Jun et al. Jul 2020 A1
20200218805 Liu et al. Jul 2020 A1
20200219517 Wang et al. Jul 2020 A1
20200220914 Carrigan et al. Jul 2020 A1
20200221155 Hansen et al. Jul 2020 A1
20200226481 Sim et al. Jul 2020 A1
20200226823 Stachniak et al. Jul 2020 A1
20200227034 Summa et al. Jul 2020 A1
20200227044 Lindahl Jul 2020 A1
20200228774 Kar et al. Jul 2020 A1
20200243069 Amores et al. Jul 2020 A1
20200243094 Thomson et al. Jul 2020 A1
20200249985 Zeitlin Aug 2020 A1
20200251111 Temkin et al. Aug 2020 A1
20200252508 Gray Aug 2020 A1
20200258508 Aggarwal et al. Aug 2020 A1
20200258512 Smith et al. Aug 2020 A1
20200258513 Smith et al. Aug 2020 A1
20200267222 Phipps et al. Aug 2020 A1
20200267503 Watkins et al. Aug 2020 A1
20200272485 Karashchuk et al. Aug 2020 A1
20200275216 Mckinney et al. Aug 2020 A1
20200279556 Gruber et al. Sep 2020 A1
20200279576 Binder et al. Sep 2020 A1
20200279627 Nida et al. Sep 2020 A1
20200285327 Hindi et al. Sep 2020 A1
20200286472 Newendorp et al. Sep 2020 A1
20200286493 Orr et al. Sep 2020 A1
20200294487 Donohoe et al. Sep 2020 A1
20200294494 Suyama et al. Sep 2020 A1
20200294508 Kwasiborski et al. Sep 2020 A1
20200298394 Han et al. Sep 2020 A1
20200301950 Theo et al. Sep 2020 A1
20200302356 Gruber et al. Sep 2020 A1
20200302919 Greborio et al. Sep 2020 A1
20200302925 Shah et al. Sep 2020 A1
20200302930 Chen et al. Sep 2020 A1
20200302932 Schramm et al. Sep 2020 A1
20200304955 Gross et al. Sep 2020 A1
20200304972 Gross et al. Sep 2020 A1
20200305084 Freeman et al. Sep 2020 A1
20200310513 Nicholson et al. Oct 2020 A1
20200312315 Li et al. Oct 2020 A1
20200312317 Kothari et al. Oct 2020 A1
20200314191 Madhavan et al. Oct 2020 A1
20200319850 Stasior et al. Oct 2020 A1
20200320592 Soule et al. Oct 2020 A1
20200320988 Rastogi et al. Oct 2020 A1
20200322571 Awai Oct 2020 A1
20200327895 Gruber et al. Oct 2020 A1
20200333875 Bansal et al. Oct 2020 A1
20200334068 Krishnamurthy et al. Oct 2020 A1
20200334492 Zheng et al. Oct 2020 A1
20200335121 Mosseri et al. Oct 2020 A1
20200342082 Sapozhnykov et al. Oct 2020 A1
20200342182 Johnson Premkumar et al. Oct 2020 A1
20200342849 Yu et al. Oct 2020 A1
20200342863 Aggarwal et al. Oct 2020 A1
20200348813 Sharifi et al. Nov 2020 A1
20200356243 Meyer et al. Nov 2020 A1
20200356589 Rekik et al. Nov 2020 A1
20200356610 Coimbra et al. Nov 2020 A1
20200356634 Srinivasan et al. Nov 2020 A1
20200357387 Prabhavalkar et al. Nov 2020 A1
20200357391 Ghoshal et al. Nov 2020 A1
20200357406 York et al. Nov 2020 A1
20200357409 Sun et al. Nov 2020 A1
20200364411 Evermann Nov 2020 A1
20200364858 Kaethner et al. Nov 2020 A1
20200365155 Milden Nov 2020 A1
20200367006 Beckhardt Nov 2020 A1
20200372633 Lee, II et al. Nov 2020 A1
20200372719 Andjelic et al. Nov 2020 A1
20200372904 Vescovi et al. Nov 2020 A1
20200372905 Wang et al. Nov 2020 A1
20200374243 Jina et al. Nov 2020 A1
20200379610 Ford et al. Dec 2020 A1
20200379640 Bellegarda et al. Dec 2020 A1
20200379726 Blatz et al. Dec 2020 A1
20200379727 Blatz et al. Dec 2020 A1
20200379728 Gada et al. Dec 2020 A1
20200380389 Eldeeb et al. Dec 2020 A1
20200380956 Rossi et al. Dec 2020 A1
20200380963 Chappidi et al. Dec 2020 A1
20200380966 Acero et al. Dec 2020 A1
20200380973 Novitchenko et al. Dec 2020 A1
20200380980 Shum et al. Dec 2020 A1
20200380984 Venkatraman et al. Dec 2020 A1
20200380985 Gada et al. Dec 2020 A1
20200382616 Vaishampayan et al. Dec 2020 A1
20200382635 Vora et al. Dec 2020 A1
20200411002 Lee et al. Dec 2020 A1
20210006943 Gross et al. Jan 2021 A1
20210011557 Lemay et al. Jan 2021 A1
20210012113 Petill et al. Jan 2021 A1
20210012775 Kang et al. Jan 2021 A1
20210012776 Peterson et al. Jan 2021 A1
20210035567 Newendorp et al. Feb 2021 A1
20210043190 Wang et al. Feb 2021 A1
20210065698 Topcu et al. Mar 2021 A1
20210067631 Van Os et al. Mar 2021 A1
20210072953 Amarilio et al. Mar 2021 A1
20210073254 Ghafourifar et al. Mar 2021 A1
20210073293 Fenton et al. Mar 2021 A1
20210074264 Liang et al. Mar 2021 A1
20210074295 Moreno et al. Mar 2021 A1
20210082400 Vishnoi et al. Mar 2021 A1
20210082420 Kraljic et al. Mar 2021 A1
20210089124 Manjunath et al. Mar 2021 A1
20210090314 Hussen et al. Mar 2021 A1
20210092128 Leblang Mar 2021 A1
20210097998 Kim et al. Apr 2021 A1
20210099317 Hilleli et al. Apr 2021 A1
20210103366 Behzadi et al. Apr 2021 A1
20210104232 Lee et al. Apr 2021 A1
20210104236 Doggett et al. Apr 2021 A1
20210105528 Van Os et al. Apr 2021 A1
20210110106 Vescovi et al. Apr 2021 A1
20210110115 Moritz et al. Apr 2021 A1
20210110254 Duy et al. Apr 2021 A1
20210117214 Presant et al. Apr 2021 A1
20210124597 Ramakrishnan et al. Apr 2021 A1
20210127031 Kanemoto Apr 2021 A1
20210127220 Mathieu et al. Apr 2021 A1
20210134318 Harvey et al. May 2021 A1
20210141839 Tang et al. May 2021 A1
20210143987 Xu et al. May 2021 A1
20210149629 Martel et al. May 2021 A1
20210149996 Bellegarda May 2021 A1
20210150151 Jiaming et al. May 2021 A1
20210151041 Gruber et al. May 2021 A1
20210151053 Takahashi et al. May 2021 A1
20210151070 Binder et al. May 2021 A1
20210152684 Weinstein et al. May 2021 A1
20210165826 Graham et al. Jun 2021 A1
20210173555 Kandur Raja et al. Jun 2021 A1
20210174020 Sohn et al. Jun 2021 A1
20210174022 Ishikawa et al. Jun 2021 A1
20210174403 Bellini et al. Jun 2021 A1
20210176521 Matthews Jun 2021 A1
20210182716 Muramoto et al. Jun 2021 A1
20210191603 Napolitano et al. Jun 2021 A1
20210191968 Orr et al. Jun 2021 A1
20210208752 Hwang Jul 2021 A1
20210208841 Wilberding Jul 2021 A1
20210210089 Ma et al. Jul 2021 A1
20210216134 Fukunaga et al. Jul 2021 A1
20210216760 Dominic et al. Jul 2021 A1
20210224032 Ryan et al. Jul 2021 A1
20210224474 Jerome et al. Jul 2021 A1
20210233532 Aram et al. Jul 2021 A1
20210247959 Agarwal et al. Aug 2021 A1
20210248804 Hussen Abdelaziz et al. Aug 2021 A1
20210249009 Manjunath et al. Aug 2021 A1
20210256980 George-Svahn et al. Aug 2021 A1
20210258554 Bruls et al. Aug 2021 A1
20210258881 Freeman et al. Aug 2021 A1
20210264913 Schramm et al. Aug 2021 A1
20210264916 Kim et al. Aug 2021 A1
20210271333 Hindi et al. Sep 2021 A1
20210273894 Tian et al. Sep 2021 A1
20210278956 Dolbakian et al. Sep 2021 A1
20210279548 Adan et al. Sep 2021 A1
20210280180 Skobeltsyn et al. Sep 2021 A1
20210281965 Malik et al. Sep 2021 A1
20210287080 Moloney Sep 2021 A1
20210294569 Piersol et al. Sep 2021 A1
20210294571 Carson et al. Sep 2021 A1
20210295602 Scapel et al. Sep 2021 A1
20210303116 Barlow Sep 2021 A1
20210303342 Dunn et al. Sep 2021 A1
20210304075 Duong et al. Sep 2021 A1
20210306812 Gross et al. Sep 2021 A1
20210312917 Weksler et al. Oct 2021 A1
20210312930 Sugaya Oct 2021 A1
20210312931 Paulik et al. Oct 2021 A1
20210313019 Pribanic et al. Oct 2021 A1
20210314440 Matias et al. Oct 2021 A1
20210318901 Gruber et al. Oct 2021 A1
20210319178 Zhang Oct 2021 A1
20210327409 Naik Oct 2021 A1
20210327410 Beaufays et al. Oct 2021 A1
20210334528 Bray et al. Oct 2021 A1
20210335342 Yuan et al. Oct 2021 A1
20210342050 Wang Nov 2021 A1
20210342212 Neumann Nov 2021 A1
20210349605 Nonaka et al. Nov 2021 A1
20210349608 Blatz et al. Nov 2021 A1
20210350799 Hansen et al. Nov 2021 A1
20210350803 Hansen et al. Nov 2021 A1
20210350810 Phipps et al. Nov 2021 A1
20210352115 Hansen et al. Nov 2021 A1
20210357172 Sinesio et al. Nov 2021 A1
20210358294 Parashar et al. Nov 2021 A1
20210365161 Ellis et al. Nov 2021 A1
20210365174 Ellis et al. Nov 2021 A1
20210365641 Zhang et al. Nov 2021 A1
20210365863 Friske et al. Nov 2021 A1
20210366473 Maeng Nov 2021 A1
20210366475 Wilkosz et al. Nov 2021 A1
20210366480 Lemay et al. Nov 2021 A1
20210373851 Stasior et al. Dec 2021 A1
20210375275 Yoon et al. Dec 2021 A1
20210375290 Hu et al. Dec 2021 A1
20210377381 Aggarwal et al. Dec 2021 A1
20210390259 Hildick-Smith et al. Dec 2021 A1
20210390955 Piernot et al. Dec 2021 A1
20210393168 Santarelli et al. Dec 2021 A1
20210398187 Narayanan et al. Dec 2021 A1
20210402306 Huang Dec 2021 A1
20210406260 Sharifi et al. Dec 2021 A1
20210407318 Pitschel et al. Dec 2021 A1
20210407502 Vescovi et al. Dec 2021 A1
20220004825 Xie et al. Jan 2022 A1
20220013106 Deng et al. Jan 2022 A1
20220019292 Lemay et al. Jan 2022 A1
20220020367 Orkin et al. Jan 2022 A1
20220021631 Jina et al. Jan 2022 A1
20220021978 Gui et al. Jan 2022 A1
20220028379 Carbune et al. Jan 2022 A1
20220028387 Walker et al. Jan 2022 A1
20220030345 Gong et al. Jan 2022 A1
20220035999 Pawelec Feb 2022 A1
20220043986 Nell et al. Feb 2022 A1
20220050661 Lange et al. Feb 2022 A1
20220067283 Bellegarda et al. Mar 2022 A1
20220068278 York et al. Mar 2022 A1
20220083986 Duffy et al. Mar 2022 A1
20220084511 Nickson et al. Mar 2022 A1
20220092262 Ni et al. Mar 2022 A1
20220093088 Sridhar et al. Mar 2022 A1
20220093095 Dighe et al. Mar 2022 A1
20220093098 Samal et al. Mar 2022 A1
20220093101 Krishnan et al. Mar 2022 A1
20220093109 Orr et al. Mar 2022 A1
20220093110 Kim et al. Mar 2022 A1
20220094765 Niewczas Mar 2022 A1
20220100789 Kumar et al. Mar 2022 A1
20220103491 Yang et al. Mar 2022 A1
20220107780 Gruber et al. Apr 2022 A1
20220114327 Faaborg et al. Apr 2022 A1
20220115016 Whalin Apr 2022 A1
20220122615 Chen et al. Apr 2022 A1
20220130126 Delgado et al. Apr 2022 A1
20220139396 Gada et al. May 2022 A1
20220148587 Drummie et al. May 2022 A1
20220155857 Lee et al. May 2022 A1
20220156041 Newendorp et al. May 2022 A1
20220157310 Newendorp et al. May 2022 A1
20220157315 Raux et al. May 2022 A1
20220180868 Sharifi et al. Jun 2022 A1
20220197491 Meyer et al. Jun 2022 A1
20220198025 Gupta et al. Jun 2022 A1
20220206298 Goodman Jun 2022 A1
20220214775 Shah et al. Jul 2022 A1
20220215159 Qian et al. Jul 2022 A1
20220222437 Lauber Jul 2022 A1
20220229985 Bellegarda et al. Jul 2022 A1
20220230653 Binder et al. Jul 2022 A1
20220253969 Kamenetskaya et al. Aug 2022 A1
20220254338 Gruber et al. Aug 2022 A1
20220254339 Acero et al. Aug 2022 A1
20220254347 Lindahl Aug 2022 A1
20220261468 Lin et al. Aug 2022 A1
20220262354 Greborio et al. Aug 2022 A1
20220264262 Gruber et al. Aug 2022 A1
20220284901 Novitchenko et al. Sep 2022 A1
20220291816 Fan et al. Sep 2022 A1
20220292128 Sharifi et al. Sep 2022 A1
20220293124 Weinberg et al. Sep 2022 A1
20220293125 Maddika et al. Sep 2022 A1
20220295170 Ito et al. Sep 2022 A1
20220300094 Hindi et al. Sep 2022 A1
20220301549 Lee et al. Sep 2022 A1
20220301566 Van Os et al. Sep 2022 A1
20220308718 Klein et al. Sep 2022 A1
20220329691 Chinthakunta et al. Oct 2022 A1
20220343066 Kwong et al. Oct 2022 A1
20220366889 Yerroju et al. Nov 2022 A1
20220374109 Kramer et al. Nov 2022 A1
20220374110 Ramaswamy et al. Nov 2022 A1
20220374597 Bellegarda et al. Nov 2022 A1
20220374727 Hansen et al. Nov 2022 A1
20220375466 Hergenrader et al. Nov 2022 A1
20220375553 Lasko et al. Nov 2022 A1
20220382843 Gong et al. Dec 2022 A1
20220382994 Cox et al. Dec 2022 A1
20220383044 Bellegarda Dec 2022 A1
20220383864 Gruber et al. Dec 2022 A1
20220383872 Li et al. Dec 2022 A1
20220391585 Bellegarda et al. Dec 2022 A1
20220392446 Webber et al. Dec 2022 A1
20220405117 Gruber et al. Dec 2022 A1
20220406301 Barros et al. Dec 2022 A1
20220406309 Piernot et al. Dec 2022 A1
20220408173 Gong et al. Dec 2022 A1
20230013615 Sanghavi et al. Jan 2023 A1
20230017115 Sanghavi et al. Jan 2023 A1
20230018457 Zeitlin Jan 2023 A1
20230026764 Karashchuk et al. Jan 2023 A1
20230029028 Aitken et al. Jan 2023 A1
20230035643 Binder et al. Feb 2023 A1
20230035941 Herman et al. Feb 2023 A1
20230036059 Blatz et al. Feb 2023 A1
20230036798 Newendorp et al. Feb 2023 A1
20230040703 Lemay et al. Feb 2023 A1
20230042224 Patel et al. Feb 2023 A1
20230048256 Gui et al. Feb 2023 A1
20230050767 Mozayeni Feb 2023 A1
20230051062 Hu et al. Feb 2023 A1
20230057442 Stasior et al. Feb 2023 A1
20230058929 Lasko et al. Feb 2023 A1
20230066552 Van Os et al. Mar 2023 A1
20230072481 Acero et al. Mar 2023 A1
20230081605 O'Mara et al. Mar 2023 A1
20230087244 Akmal et al. Mar 2023 A1
20230098174 Simes et al. Mar 2023 A1
20230111509 Kim et al. Apr 2023 A1
20230112859 Vilhauer et al. Apr 2023 A1
20230134970 Rasipuram et al. May 2023 A1
Foreign Referenced Citations (677)
Number Date Country
2014100581 Sep 2014 AU
2015203483 Jul 2015 AU
2015101171 Oct 2015 AU
2017203668 Jan 2018 AU
2018100187 Mar 2018 AU
2017222436 Oct 2018 AU
2666438 Jun 2013 CA
709795 Dec 2015 CH
1641563 Jul 2005 CN
101709977 May 2010 CN
101872156 Oct 2010 CN
102057374 May 2011 CN
102243692 Nov 2011 CN
102647628 Aug 2012 CN
202385210 Aug 2012 CN
102693047 Sep 2012 CN
102792320 Nov 2012 CN
102857808 Jan 2013 CN
102859480 Jan 2013 CN
102866828 Jan 2013 CN
102870065 Jan 2013 CN
102882752 Jan 2013 CN
102890936 Jan 2013 CN
102893327 Jan 2013 CN
102915731 Feb 2013 CN
102917004 Feb 2013 CN
102917271 Feb 2013 CN
102918493 Feb 2013 CN
102939515 Feb 2013 CN
102955652 Mar 2013 CN
103035240 Apr 2013 CN
103035251 Apr 2013 CN
103038728 Apr 2013 CN
103064956 Apr 2013 CN
103078995 May 2013 CN
103093334 May 2013 CN
103093755 May 2013 CN
103105995 May 2013 CN
103109249 May 2013 CN
103135916 Jun 2013 CN
103187053 Jul 2013 CN
103197963 Jul 2013 CN
103198831 Jul 2013 CN
103209369 Jul 2013 CN
103217892 Jul 2013 CN
103226949 Jul 2013 CN
103236260 Aug 2013 CN
103246638 Aug 2013 CN
103268315 Aug 2013 CN
103277974 Sep 2013 CN
103280218 Sep 2013 CN
103282957 Sep 2013 CN
103292437 Sep 2013 CN
103324100 Sep 2013 CN
103327063 Sep 2013 CN
103365279 Oct 2013 CN
103366741 Oct 2013 CN
203249629 Oct 2013 CN
103390016 Nov 2013 CN
103412789 Nov 2013 CN
103414949 Nov 2013 CN
103426428 Dec 2013 CN
103455234 Dec 2013 CN
103456303 Dec 2013 CN
103456304 Dec 2013 CN
103456306 Dec 2013 CN
103457837 Dec 2013 CN
103475551 Dec 2013 CN
103477592 Dec 2013 CN
103533143 Jan 2014 CN
103533154 Jan 2014 CN
103543902 Jan 2014 CN
103546453 Jan 2014 CN
103562863 Feb 2014 CN
103582896 Feb 2014 CN
103593054 Feb 2014 CN
103608859 Feb 2014 CN
103620605 Mar 2014 CN
103645876 Mar 2014 CN
103677261 Mar 2014 CN
103686723 Mar 2014 CN
103714816 Apr 2014 CN
103716454 Apr 2014 CN
103727948 Apr 2014 CN
103730120 Apr 2014 CN
103744761 Apr 2014 CN
103748531 Apr 2014 CN
103760984 Apr 2014 CN
103761104 Apr 2014 CN
103765385 Apr 2014 CN
103778527 May 2014 CN
103780758 May 2014 CN
103792985 May 2014 CN
103794212 May 2014 CN
103795850 May 2014 CN
103809548 May 2014 CN
103841268 Jun 2014 CN
103885663 Jun 2014 CN
103902373 Jul 2014 CN
103930945 Jul 2014 CN
103942932 Jul 2014 CN
103959751 Jul 2014 CN
203721183 Jul 2014 CN
103971680 Aug 2014 CN
104007832 Aug 2014 CN
102693729 Sep 2014 CN
104036774 Sep 2014 CN
104038621 Sep 2014 CN
104050153 Sep 2014 CN
104090652 Oct 2014 CN
104092829 Oct 2014 CN
104113471 Oct 2014 CN
104125322 Oct 2014 CN
104144377 Nov 2014 CN
104145304 Nov 2014 CN
104169837 Nov 2014 CN
104180815 Dec 2014 CN
104185868 Dec 2014 CN
104219785 Dec 2014 CN
104240701 Dec 2014 CN
104243699 Dec 2014 CN
104281259 Jan 2015 CN
104281390 Jan 2015 CN
104284257 Jan 2015 CN
104284486 Jan 2015 CN
104335205 Feb 2015 CN
104335207 Feb 2015 CN
104335234 Feb 2015 CN
104350454 Feb 2015 CN
104360990 Feb 2015 CN
104374399 Feb 2015 CN
104378723 Feb 2015 CN
104423625 Mar 2015 CN
104423780 Mar 2015 CN
104427104 Mar 2015 CN
104463552 Mar 2015 CN
104464733 Mar 2015 CN
104487929 Apr 2015 CN
104516522 Apr 2015 CN
104520849 Apr 2015 CN
104573472 Apr 2015 CN
104575493 Apr 2015 CN
104575501 Apr 2015 CN
104575504 Apr 2015 CN
104584010 Apr 2015 CN
104584096 Apr 2015 CN
104584601 Apr 2015 CN
104604274 May 2015 CN
104679472 Jun 2015 CN
104685898 Jun 2015 CN
104699746 Jun 2015 CN
104731441 Jun 2015 CN
104769584 Jul 2015 CN
104769670 Jul 2015 CN
104798012 Jul 2015 CN
104821167 Aug 2015 CN
104821934 Aug 2015 CN
104836909 Aug 2015 CN
104854583 Aug 2015 CN
104867492 Aug 2015 CN
104869342 Aug 2015 CN
104951077 Sep 2015 CN
104967748 Oct 2015 CN
104969289 Oct 2015 CN
104978963 Oct 2015 CN
105025051 Nov 2015 CN
105027197 Nov 2015 CN
105093526 Nov 2015 CN
105100356 Nov 2015 CN
105144136 Dec 2015 CN
105164678 Dec 2015 CN
105164719 Dec 2015 CN
105190607 Dec 2015 CN
105247511 Jan 2016 CN
105247551 Jan 2016 CN
105264524 Jan 2016 CN
105264903 Jan 2016 CN
105265005 Jan 2016 CN
105278681 Jan 2016 CN
105320251 Feb 2016 CN
105320726 Feb 2016 CN
105338425 Feb 2016 CN
105379234 Mar 2016 CN
105427122 Mar 2016 CN
105430186 Mar 2016 CN
105468137 Apr 2016 CN
105471705 Apr 2016 CN
105472587 Apr 2016 CN
105516441 Apr 2016 CN
105554217 May 2016 CN
105556592 May 2016 CN
105677765 Jun 2016 CN
105791920 Jul 2016 CN
105808200 Jul 2016 CN
105830048 Aug 2016 CN
105869641 Aug 2016 CN
105872222 Aug 2016 CN
105917311 Aug 2016 CN
106030699 Oct 2016 CN
106062734 Oct 2016 CN
106062790 Oct 2016 CN
106164909 Nov 2016 CN
106415412 Feb 2017 CN
106462383 Feb 2017 CN
106462617 Feb 2017 CN
106463114 Feb 2017 CN
106465074 Feb 2017 CN
106471570 Mar 2017 CN
106534469 Mar 2017 CN
106558310 Apr 2017 CN
106575195 Apr 2017 CN
106575501 Apr 2017 CN
106773742 May 2017 CN
106776581 May 2017 CN
107004412 Aug 2017 CN
107450800 Dec 2017 CN
107480161 Dec 2017 CN
107491285 Dec 2017 CN
107491468 Dec 2017 CN
107491469 Dec 2017 CN
107506037 Dec 2017 CN
107545262 Jan 2018 CN
107608998 Jan 2018 CN
107615378 Jan 2018 CN
107623616 Jan 2018 CN
107786730 Mar 2018 CN
107852436 Mar 2018 CN
107871500 Apr 2018 CN
107919123 Apr 2018 CN
107924313 Apr 2018 CN
107978313 May 2018 CN
108268187 Jul 2018 CN
108647681 Oct 2018 CN
109447234 Mar 2019 CN
109657629 Apr 2019 CN
110135411 Aug 2019 CN
110263144 Sep 2019 CN
105164719 Nov 2019 CN
110531860 Dec 2019 CN
110598671 Dec 2019 CN
110647274 Jan 2020 CN
110825469 Feb 2020 CN
110945840 Mar 2020 CN
111124224 May 2020 CN
107123417 Jun 2020 CN
111316203 Jun 2020 CN
112204507 Jan 2021 CN
202016008226 May 2017 DE
2551784 Jan 2013 EP
2555536 Feb 2013 EP
2575128 Apr 2013 EP
2608610 Jun 2013 EP
2632129 Aug 2013 EP
2639792 Sep 2013 EP
2669889 Dec 2013 EP
2672229 Dec 2013 EP
2672231 Dec 2013 EP
2675147 Dec 2013 EP
2680257 Jan 2014 EP
2683147 Jan 2014 EP
2683175 Jan 2014 EP
2672231 Apr 2014 EP
2717259 Apr 2014 EP
2725577 Apr 2014 EP
2733598 May 2014 EP
2733896 May 2014 EP
2741175 Jun 2014 EP
2743846 Jun 2014 EP
2760015 Jul 2014 EP
2779160 Sep 2014 EP
2781883 Sep 2014 EP
2787683 Oct 2014 EP
2801890 Nov 2014 EP
2801972 Nov 2014 EP
2801974 Nov 2014 EP
2824564 Jan 2015 EP
2849177 Mar 2015 EP
2879402 Jun 2015 EP
2881939 Jun 2015 EP
2891049 Jul 2015 EP
2915021 Sep 2015 EP
2930715 Oct 2015 EP
2938022 Oct 2015 EP
2940556 Nov 2015 EP
2947859 Nov 2015 EP
2950307 Dec 2015 EP
2957986 Dec 2015 EP
2973380 Jan 2016 EP
2985984 Feb 2016 EP
2988513 Feb 2016 EP
2891049 Mar 2016 EP
3032532 Jun 2016 EP
3035329 Jun 2016 EP
3036594 Jun 2016 EP
3038333 Jun 2016 EP
3107101 Dec 2016 EP
3115905 Jan 2017 EP
3125097 Feb 2017 EP
3132442 Feb 2017 EP
2672231 May 2017 EP
3161612 May 2017 EP
3200185 Aug 2017 EP
3224708 Oct 2017 EP
3227771 Oct 2017 EP
3246916 Nov 2017 EP
3270658 Jan 2018 EP
3300074 Mar 2018 EP
3336805 Jun 2018 EP
2973380 Aug 2018 EP
2983065 Aug 2018 EP
3382530 Oct 2018 EP
3392876 Oct 2018 EP
3401773 Nov 2018 EP
2973002 Jun 2019 EP
3506151 Jul 2019 EP
3550483 Oct 2019 EP
3567584 Nov 2019 EP
3588912 Jan 2020 EP
3323058 Feb 2020 EP
3321928 Apr 2020 EP
2992490 Feb 2021 EP
4131256 Feb 2023 EP
2013-37688 Feb 2013 JP
2013-46171 Mar 2013 JP
2013-511214 Mar 2013 JP
2013-65284 Apr 2013 JP
2013-73240 Apr 2013 JP
2013-513315 Apr 2013 JP
2013-80476 May 2013 JP
2013-88535 May 2013 JP
2013-517566 May 2013 JP
2013-131087 Jul 2013 JP
2013-134430 Jul 2013 JP
2013-134729 Jul 2013 JP
2013-140520 Jul 2013 JP
2013-527947 Jul 2013 JP
2013-528012 Jul 2013 JP
2013-148419 Aug 2013 JP
2013-156349 Aug 2013 JP
2013-174987 Sep 2013 JP
2013-535059 Sep 2013 JP
2013-200265 Oct 2013 JP
2013-200423 Oct 2013 JP
2013-205999 Oct 2013 JP
2013-231655 Nov 2013 JP
2013-238935 Nov 2013 JP
2013-238936 Nov 2013 JP
2013-248292 Dec 2013 JP
2013-257694 Dec 2013 JP
2013-258600 Dec 2013 JP
2014-2586 Jan 2014 JP
2014-10688 Jan 2014 JP
2014-502445 Jan 2014 JP
2014-26629 Feb 2014 JP
2014-45449 Mar 2014 JP
2014-507903 Mar 2014 JP
2014-60600 Apr 2014 JP
2014-72586 Apr 2014 JP
2014-77969 May 2014 JP
2014-89711 May 2014 JP
2014-109889 Jun 2014 JP
2014-124332 Jul 2014 JP
2014-126600 Jul 2014 JP
2014-127754 Jul 2014 JP
2014-140121 Jul 2014 JP
2014-518409 Jul 2014 JP
2014-142566 Aug 2014 JP
2014-145842 Aug 2014 JP
2014-146940 Aug 2014 JP
2014-150323 Aug 2014 JP
2014-519648 Aug 2014 JP
2014-182042 Sep 2014 JP
2014-524627 Sep 2014 JP
2014-191272 Oct 2014 JP
2014-219614 Nov 2014 JP
2014-222514 Nov 2014 JP
2015-1931 Jan 2015 JP
2015-4928 Jan 2015 JP
2015-8001 Jan 2015 JP
2015-10979 Jan 2015 JP
2015-12301 Jan 2015 JP
2015-18365 Jan 2015 JP
2015-501022 Jan 2015 JP
2015-501034 Jan 2015 JP
2015-504619 Feb 2015 JP
2015-41845 Mar 2015 JP
2015-52500 Mar 2015 JP
2015-60423 Mar 2015 JP
2015-81971 Apr 2015 JP
2015-83938 Apr 2015 JP
2015-94848 May 2015 JP
2015-514254 May 2015 JP
2015-519675 Jul 2015 JP
2015-520409 Jul 2015 JP
2015-524974 Aug 2015 JP
2015-526776 Sep 2015 JP
2015-527683 Sep 2015 JP
2015-528140 Sep 2015 JP
2015-528918 Oct 2015 JP
2015-531909 Nov 2015 JP
2016-504651 Feb 2016 JP
2016-35614 Mar 2016 JP
2016-508007 Mar 2016 JP
2016-71247 May 2016 JP
2016-119615 Jun 2016 JP
2016-151928 Aug 2016 JP
2016-524193 Aug 2016 JP
2016-156845 Sep 2016 JP
2016-536648 Nov 2016 JP
2017-11608 Jan 2017 JP
2017-19331 Jan 2017 JP
2017-516153 Jun 2017 JP
2017-123187 Jul 2017 JP
2017-211608 Nov 2017 JP
2017-537361 Dec 2017 JP
6291147 Feb 2018 JP
2018-64297 Apr 2018 JP
2018-511095 Apr 2018 JP
2018-101242 Jun 2018 JP
2018-113035 Jul 2018 JP
2018-525950 Sep 2018 JP
2018-536889 Dec 2018 JP
10-2013-0035983 Apr 2013 KR
10-2013-0086750 Aug 2013 KR
10-2013-0090947 Aug 2013 KR
10-2013-0108563 Oct 2013 KR
10-1334342 Nov 2013 KR
10-2013-0131252 Dec 2013 KR
10-2013-0133629 Dec 2013 KR
10-2014-0007282 Jan 2014 KR
10-2014-0024271 Feb 2014 KR
10-2014-0025996 Mar 2014 KR
10-2014-0031283 Mar 2014 KR
10-2014-0033574 Mar 2014 KR
10-2014-0042994 Apr 2014 KR
10-2014-0048779 Apr 2014 KR
10-2014-0055204 May 2014 KR
10-2014-0059697 May 2014 KR
10-2014-0068752 Jun 2014 KR
10-2014-0071208 Jun 2014 KR
10-2014-0088449 Jul 2014 KR
10-2014-0093949 Jul 2014 KR
10-2014-0106715 Sep 2014 KR
10-2014-0107253 Sep 2014 KR
10-2014-0147557 Dec 2014 KR
10-2015-0006454 Jan 2015 KR
10-2015-0013631 Feb 2015 KR
10-2015-0025059 Mar 2015 KR
10-1506510 Mar 2015 KR
10-2015-0038375 Apr 2015 KR
10-2015-0039380 Apr 2015 KR
10-2015-0041974 Apr 2015 KR
10-2015-0043512 Apr 2015 KR
10-1510013 Apr 2015 KR
10-2015-0062811 Jun 2015 KR
10-2015-0095624 Aug 2015 KR
10-1555742 Sep 2015 KR
10-2015-0113127 Oct 2015 KR
10-2015-0131262 Nov 2015 KR
10-2015-0138109 Dec 2015 KR
10-2016-0004351 Jan 2016 KR
10-2016-0010523 Jan 2016 KR
10-2016-0040279 Apr 2016 KR
10-2016-0055839 May 2016 KR
10-2016-0065503 Jun 2016 KR
10-2016-0101079 Aug 2016 KR
10-2016-0101198 Aug 2016 KR
10-2016-0105847 Sep 2016 KR
10-2016-0121585 Oct 2016 KR
10-2016-0127165 Nov 2016 KR
10-2016-0140694 Dec 2016 KR
10-2016-0147854 Dec 2016 KR
10-2017-0004482 Jan 2017 KR
10-2017-0036805 Apr 2017 KR
10-2017-0096774 Aug 2017 KR
10-2017-0104006 Sep 2017 KR
10-2017-0107058 Sep 2017 KR
10-1776673 Sep 2017 KR
10-2018-0032632 Mar 2018 KR
10-2018-0034637 Apr 2018 KR
10-2018-0122837 Nov 2018 KR
10-2018-0133525 Dec 2018 KR
10-2018-0135877 Dec 2018 KR
10-1959328 Mar 2019 KR
10-2020-0007926 Jan 2020 KR
10-2020-0105519 Sep 2020 KR
2012141604 Apr 2014 RU
201312548 Mar 2013 TW
201407184 Feb 2014 TW
201610982 Mar 2016 TW
201629750 Aug 2016 TW
2010002497 Jan 2010 WO
2011084156 Jul 2011 WO
2011088053 Jul 2011 WO
2011095523 Aug 2011 WO
2011116309 Sep 2011 WO
2012033312 Mar 2012 WO
2012092562 Jul 2012 WO
2012145227 Oct 2012 WO
2012167168 Dec 2012 WO
2012173902 Dec 2012 WO
2013009578 Jan 2013 WO
2013022135 Feb 2013 WO
2013022223 Feb 2013 WO
2013048880 Apr 2013 WO
2013049358 Apr 2013 WO
2013057153 Apr 2013 WO
2013101489 Jul 2013 WO
2013118988 Aug 2013 WO
2013122310 Aug 2013 WO
2013128999 Sep 2013 WO
2013133533 Sep 2013 WO
2013137660 Sep 2013 WO
2013163113 Oct 2013 WO
2013163857 Nov 2013 WO
2013169842 Nov 2013 WO
2013173504 Nov 2013 WO
2013173511 Nov 2013 WO
2013176847 Nov 2013 WO
2013184953 Dec 2013 WO
2013184990 Dec 2013 WO
2014003138 Jan 2014 WO
2014004544 Jan 2014 WO
2014008461 Jan 2014 WO
2014018580 Jan 2014 WO
2014021967 Feb 2014 WO
2014022148 Feb 2014 WO
2014028735 Feb 2014 WO
2014028797 Feb 2014 WO
2014031505 Feb 2014 WO
2014032461 Mar 2014 WO
2014040022 Mar 2014 WO
2014046475 Mar 2014 WO
2014047047 Mar 2014 WO
2014048855 Apr 2014 WO
2014066352 May 2014 WO
2014070872 May 2014 WO
2014073825 May 2014 WO
2014078965 May 2014 WO
2014093339 Jun 2014 WO
2014093911 Jun 2014 WO
2014096506 Jun 2014 WO
2014124332 Aug 2014 WO
2014137074 Sep 2014 WO
2014138604 Sep 2014 WO
2014143959 Sep 2014 WO
2014144395 Sep 2014 WO
2014144579 Sep 2014 WO
2014144949 Sep 2014 WO
2014149473 Sep 2014 WO
2014151153 Sep 2014 WO
2014124332 Oct 2014 WO
2014159578 Oct 2014 WO
2014159581 Oct 2014 WO
2014162570 Oct 2014 WO
2014169269 Oct 2014 WO
2014173189 Oct 2014 WO
2013173504 Dec 2014 WO
2014197336 Dec 2014 WO
2014197339 Dec 2014 WO
2014197635 Dec 2014 WO
2014197730 Dec 2014 WO
2014200728 Dec 2014 WO
2014200731 Dec 2014 WO
2014203495 Dec 2014 WO
2014204659 Dec 2014 WO
2014209264 Dec 2014 WO
2014210392 Dec 2014 WO
2015018440 Feb 2015 WO
2015020942 Feb 2015 WO
2015029379 Mar 2015 WO
2015030796 Mar 2015 WO
2015036817 Mar 2015 WO
2015041882 Mar 2015 WO
2015041892 Mar 2015 WO
2015047932 Apr 2015 WO
2015053485 Apr 2015 WO
2015054141 Apr 2015 WO
2015080530 Jun 2015 WO
2015084659 Jun 2015 WO
2015092943 Jun 2015 WO
2015094169 Jun 2015 WO
2015094369 Jun 2015 WO
2015098306 Jul 2015 WO
2015099939 Jul 2015 WO
2015112625 Jul 2015 WO
2015116151 Aug 2015 WO
2015121449 Aug 2015 WO
2015127404 Aug 2015 WO
2015151133 Oct 2015 WO
2015153310 Oct 2015 WO
2015157013 Oct 2015 WO
2015183368 Dec 2015 WO
2015183401 Dec 2015 WO
2015183699 Dec 2015 WO
2015184186 Dec 2015 WO
2015184387 Dec 2015 WO
2015200207 Dec 2015 WO
2016004074 Jan 2016 WO
2016027933 Feb 2016 WO
2016028946 Feb 2016 WO
2016033257 Mar 2016 WO
2016039992 Mar 2016 WO
2016040721 Mar 2016 WO
2016045192 Mar 2016 WO
2016048789 Mar 2016 WO
2016049439 Mar 2016 WO
2016051519 Apr 2016 WO
2016052164 Apr 2016 WO
2016054230 Apr 2016 WO
2016057268 Apr 2016 WO
2016075081 May 2016 WO
2016085775 Jun 2016 WO
2016085776 Jun 2016 WO
2016089029 Jun 2016 WO
2016100139 Jun 2016 WO
2016111881 Jul 2016 WO
2016118344 Jul 2016 WO
2016144840 Sep 2016 WO
2016144982 Sep 2016 WO
2016144983 Sep 2016 WO
2016175354 Nov 2016 WO
2016187149 Nov 2016 WO
2016190950 Dec 2016 WO
2016191737 Dec 2016 WO
2016209444 Dec 2016 WO
2016209924 Dec 2016 WO
2017044160 Mar 2017 WO
2017044257 Mar 2017 WO
2017044260 Mar 2017 WO
2017044629 Mar 2017 WO
2017053311 Mar 2017 WO
2017058293 Apr 2017 WO
2017059388 Apr 2017 WO
2017071420 May 2017 WO
2017142116 Aug 2017 WO
2017160487 Sep 2017 WO
2017200777 Nov 2017 WO
2017203484 Nov 2017 WO
2017210035 Dec 2017 WO
2017213678 Dec 2017 WO
2017213682 Dec 2017 WO
2017218194 Dec 2017 WO
2018009397 Jan 2018 WO
2018014788 Jan 2018 WO
2018044633 Mar 2018 WO
2018057269 Mar 2018 WO
2018067528 Apr 2018 WO
2018075170 Apr 2018 WO
2018081833 May 2018 WO
2018090060 May 2018 WO
2018176053 Sep 2018 WO
2018208506 Nov 2018 WO
2018209152 Nov 2018 WO
2018213401 Nov 2018 WO
2018213415 Nov 2018 WO
2018213481 Nov 2018 WO
2018217014 Nov 2018 WO
2018231307 Dec 2018 WO
2019067930 Apr 2019 WO
2019078576 Apr 2019 WO
2019079017 Apr 2019 WO
2019143397 Jul 2019 WO
2019147429 Aug 2019 WO
2019190646 Oct 2019 WO
2019236217 Dec 2019 WO
2020010530 Jan 2020 WO
2020022572 Jan 2020 WO
2020096706 May 2020 WO
2020109074 Jun 2020 WO
2020208302 Oct 2020 WO
2021054565 Mar 2021 WO
2021061349 Apr 2021 WO
2021062148 Apr 2021 WO
2021188439 Sep 2021 WO
2021252230 Dec 2021 WO
2022047214 Mar 2022 WO
Non-Patent Literature Citations (347)
Entry
Advisory Action received for U.S. Appl. No. 16/024,447, mailed on Jan. 28, 2020, 7 pages.
“Alexa, Turn Up the Heat!, Smartthings Samsung [online]”, Online available at:—<https://web.archive.org/web/20160329142041/https://blog.smartthings.com/news/smartthingsupdates/alexa-turn-up-the-heat/>, Mar. 3, 2016, 3 pages.
Alsharif et al., “Long Short-Term Memory Neural Network for Keyboard Gesture Decoding”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia, Sep. 2015, 5 pages.
Anania Peter, “Amazon Echo with Home Automation (Smartthings)”, Online available at:—<https://www.youtube.com/watch?v=LMW6aXmsWNE>, Dec. 20, 2015, 1 page.
Android Authority, “How to use Tasker: A Beginner's Guide”, Online available at:—<https://youtube.com/watch?v= rDpdS_YWzFc>, May 1, 2013, 1 page.
Apple Differential Privacy Team, “Learning with Privacy at Scale”, Apple Machine Learning Blog, vol. 1, No. 8, Online available at: <https://machinelearning.apple.com/2017/12/06/learning-with-privacy-at-scale.html>, Dec. 2017, 9 pages.
Apple, “VoiceOver for OS X”, Online available at:—<http://www.apple.com/accessibility/voiceover/>, May 19, 2014, pp. 1-3.
Applicant Initiated Interview Summary received for U.S. Appl. No. 16/024,447, mailed on Oct. 2, 2019, 4 pages.
Applicant-Initiated Interview Summary received for U.S. Appl. No. 16/024,447, mailed on Jan. 17, 2020, 4 pages.
Applicant-Initiated Interview Summary received for U.S. Appl. No. 16/402,922, mailed on Apr. 28, 2020, 3 pages.
Applicant-Initiated Interview Summary received for U.S. Appl. No. 16/402,922, mailed on Jan. 17, 2020, 3 pages.
Applicant-Initiated Interview Summary received for U.S. Appl. No. 16/717,790, mailed on Dec. 15, 2020, 3 pages.
Asakura et al., “What LG thinks; How the TV should be in the Living Room”, HiVi, vol. 31, No. 7, Stereo Sound Publishing, Inc., Jun. 17, 2013, pp. 68-71.
“Ask Alexa—Things That Are Smart Wiki”, Online available at:—<http://thingsthataresmart.wiki/index.php?title=Ask_Alexa&oldid=4283>, Jun. 8, 2016, pp. 1-31.
Ashingtondctech & Gaming, “SwipeStatusBar—Reveal the Status Bar in a Fullscreen App”, Online Available at: <https://www.youtube.com/watch?v=wA_tT9|AreQ>, Jul. 1, 2013, 3 pages.
Automate Your Life, “How to Setup Google Home Routines—A Google Home Routines Walkthrough”, Online Available at: <https://www.youtube.com/watch?v=pXokZHP9kZg>, Aug. 12, 2018, 1 page.
Bell, Jason, “Machine Learning Hands-On for Developers and Technical Professionals”, Wiley, 2014, 82 pages.
Bellegarda, Jeromer, “Chapter 1: Spoken Language Understanding for Natural Interaction: The Siri Experience”, Natural Interaction with Robots, Knowbots and Smartphones, 2014, pp. 3-14.
Beointegration.com, “BeoLink Gateway—Programming Example”, Online Available at: < https:/ /www.youtube.com/watch?v=TXDaJFm5UH4>, Mar. 4, 2015, 3 pages.
Bodapati et al., “Neural Word Decomposition Models for Abusive Language Detection”, Proceedings of the Third Workshop on Abusive Language Online, Aug. 1, 2019, pp. 135-145.
Brief Communication Regarding Oral Proceedings received for European Patent Application No. 16904830.3, mailed on Feb. 3, 2021, 1 page.
Brief Communication Regarding Oral Proceedings received for European Patent Application No. 19150734.2, mailed on Nov. 17, 2020, 2 pages.
Brief Communication Regarding Oral Proceedings received for European Patent Application No. 19157463.1, mailed on Mar. 8, 2021, 2 pages.
Burgess, Brian, “Amazon Echo Tip: Enable the Wake Up Sound”, Online available at:—<https://www.groovypost.com/howto/amazon-echo-tip-enable-wake-up-sound/>, Jun. 30, 2015, 4 pages.
Cambria et al., “Jumping NLP curves: A Review of Natural Language Processing Research.”, IEEE Computational Intelligence magazine, 2014, vol. 9, May 2014, pp. 48-57.
Chang et al., “Monaural Multi-Talker Speech Recognition with Attention Mechanism and Gated Convolutional Networks”, Interspeech 2018, Sep. 2-6, 2018, pp. 1586-1590.
Chen et al., “A Convolutional Neural Network with Dynamic Correlation Pooling”, 13th International Conference on Computational Intelligence and Security, IEEE, 2017, pp. 496-499.
Chen et al., “Progressive Joint Modeling in Unsupervised Single-Channel Overlapped Speech Recognition”, IEEE/ACM Transactions on Audio, Speech, And Language Processing, vol. 26, No. 1, Jan. 2018, pp. 184-196.
Chen, Angela, “Amazon's Alexa now handles patient health information”, Available online at: <https://www.theverge.com/2019/4/4/18295260/amazon-hipaa-alexa-echo-patient-health-information-privacy-voice-assistant>, Apr. 4, 2019, 2 pages.
Chenghao, Yuan, “MacroDroid”, Online available at: https://www.ifanr.com/weizhizao/612531, Jan. 25, 2016, 7 pages.
Colt, Sam, “Here's One Way Apple's Smartwatch Could Be Better Than Anything Else”, Business Insider, Aug. 21, 2014, pp. 1-4.
Conneau et al., “Supervised Learning of Universal Sentence Representations from Natural Language Inference Data”, Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Copenhagen, Denmark, Sep. 7-11, 2017, pp. 670-680.
Corrected Notice of Allowance received for U.S. Appl. No. 15/271,766, mailed on Dec. 4, 2019, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 15/271,766, mailed on Jan. 28, 2020, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 15/271,766, mailed on Oct. 15, 2019, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 15/271,766, mailed on Sep. 30, 2019, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 16/402,922, mailed on Jul. 8, 2020, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 16/402,922, mailed on Oct. 27, 2020, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 16/402,922, mailed on Sep. 17, 2020, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 16/402,922, mailed on Sep. 28, 2020, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 16/717,790, mailed on Apr. 12, 2021, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 16/717,790, mailed on Apr. 28, 2021, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 16/717,790, mailed on Feb. 12, 2021, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 16/717,790, mailed on Mar. 8, 2021, 2 pages.
Corrected Notice of Allowance received for U.S. Appl. No. 16/717,790, mailed on Mar. 24, 2021, 2 pages.
Czech Lucas, “A System for Recognizing Natural Spelling of English Words”, Diploma Thesis, Karlsruhe Institute of Technology, May 7, 2014, 107 pages.
Dai, et al., “Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context”, Online available at: arXiv:1901.02860v3, Jun. 2, 2019, 20 pages.
Decision to Grant received for Danish Patent Application No. PA201770032, mailed on May 22, 2019, 2 pages.
Decision to Grant received for Danish Patent Application No. PA201770035, mailed on Jun. 21, 2019, 2 pages.
Decision to Grant received for Danish Patent Application No. PA201770036, mailed on Oct. 8, 2018, 2 pages.
Decision to Grant received for European Patent Application No. 19150734.2, mailed on Apr. 22, 2021, 2 pages.
Decision to Grant received for European Patent Application No. 19157463.1, mailed on Jun. 30, 2022, 2 pages.
Decision to Refuse received for European Patent Application No. 16904830.3, mailed on Mar. 24, 2021, 20 pages.
Deedeevuu, “Amazon Echo Alarm Feature”, Online available at:—<https://www.youtube.com/watch?v=fdjU8eRLk7c>, Feb. 16, 2015, 1 page.
Delcroix et al., “Context Adaptive Deep Neural Networks For Fast Acoustic Model Adaptation”, ICASSP, 2015, pp. 4535-4539.
Delcroix et al., “Context Adaptive Neural Network for Rapid Adaptation of Deep CNN Based Acoustic Models”, Interspeech 2016, Sep. 8-12, 2016, pp. 1573-1577.
Derrick, Amanda, “How to Set Up Google Home for Multiple Users”, Lifewire, Online available at:—<https://www.lifewire.com/set-up-google-home-multiple-users-4685691>, Jun. 8, 2020, 9 pages.
Dighe et al., “Lattice-Based Improvements for Voice Triggering Using Graph Neural Networks”, in 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jan. 25, 2020, 5 pages.
Dihelson, “How Can I Use Voice or Phrases as Triggers to Macrodroid?”, Macrodroid Forums, Online Available at:—<https://www.tapatalk.com/groups/macrodroid/how-can-i-use-voice-or-phrases-as-triggers-to-macr-t4845.html>, May 9, 2018, 5 pages.
“DIRECTV™ Voice”, Now Part of the DIRECTTV Mobile App for Phones, Sep. 18, 2013, 5 pages.
Dwork et al., “The Algorithmic Foundations of Differential Privacy”, Foundations and Trends in Theoretical Computer Science: vol. 9: No. 3-4, 211-407, 2014, 281 pages.
Earthling 1984, “Samsung Galaxy Smart Stay Feature Explained”, Online available at:—<https://www.youtube.com/watch?v=RpjBNtSjupl>, May 29, 2013, 1 page.
Eder et al., “At the Lower End of Language—Exploring the Vulgar and Obscene Side of German”, Proceedings of the Third Workshop on Abusive Language Online, Florence, Italy, Aug. 1, 2019, pp. 119-128.
Edim, et al., “A Multi-Agent Based Virtual Personal Assistant for E-Health Service”, Journal of Information Engineering and Applications, vol. 3, No. 11, 2013, 9 pages.
Extended European Search Report received for European Patent Application No. 16904830.3, mailed on Jun. 24, 2019, 8 pages.
Extended European Search Report received for European Patent Application No. 19150734.2, mailed on Apr. 26, 2019, 8 pages.
Extended European Search Report received for European Patent Application No. 19157463.1, mailed on Jun. 6, 2019, 8 pages.
Filipowicz, Luke, “How to use the QuickType keyboard in iOS 8”, Online available at:—<https://www.imore.com/comment/568232>, Oct. 11, 2014, pp. 1-17.
Final Office Action received for U.S. Appl. No. 16/024,447, mailed on Oct. 11, 2019, 59 pages.
Final Office Action received for U.S. Appl. No. 16/402,922, mailed on Jan. 31, 2020, 22 pages.
Final Office Action Received for U.S. Appl. No. 15/271,766, mailed on Mar. 11, 2019, 17 pages.
Gadget Hacks, “Tasker Too Complicated? Give MacroDroid a Try [How-To]”, Online available at: <https://www.youtube.com/watch?v=8YL9cWCykKc>, May 27, 2016, 1 page.
“Galaxy S7: How to Adjust Screen Timeout & Lock Screen Timeout”, Online available at:—<https://www.youtube.com/watch?v=n6e1WKUS2ww>, Jun. 9, 2016, 1 page.
Gatys et al., “Image Style Transfer Using Convolutional Neural Networks”, Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016, pp. 2414-2423.
Ghauth et al., “Text Censoring System for Filtering Malicious Content Using Approximate String Matching and Bayesian Filtering”, Proc. 4th INNS Symposia Series on Computational Intelligence in Information Systems, Bandar Seri Begawan, Brunei, 2015, pp. 149-158.
Goodfellow et al., “Generative Adversarial Networks”, Proceedings of the Neural Information Processing Systems, Dec. 2014, 9 pages.
Google Developers, “Voice search in your app”, Online available at:—<https://www.youtube.com/watch?v=PS1FbB5qWEI>, Nov. 12, 2014, 1 page.
Gu et al., “BadNets: Evaluating Backdooring Attacks on Deep Neural Networks”, IEEE Access, vol. 7, Mar. 21, 2019, pp. 47230-47244.
Guim, Mark, “How to Set a Person-Based Reminder with Cortana”, Online available at:—<http://www.wpcentral.com/how-to-person-based-reminder-cortana>, Apr. 26, 2014, 15 pages.
Guo et al., “Time-Delayed Bottleneck Highway Networks Using a DFT Feature for Keyword Spotting”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018, 5 pages.
Gupta et al., “I-vector-based Speaker Adaptation of Deep Neural Networks for French Broadcast Audio Transcription”, ICASSP, 2014, 2014, pp. 6334-6338.
Gupta, Naresh, “Inside Bluetooth Low Energy”, Artech House, 2013, 274 pages.
Haung et al., “A Study for Improving Device-Directed Speech Detection Toward Frictionless Human-Machine Interaction”, in Proc. Interspeech, 2019, 5 pages.
“Headset Button Controller v7.3 APK Full APP Download for Andriod, Blackberry, iPhone”, Online available at:—<http://fullappdownload.com/headset-button-controller-v7-3-apk/>, Jan. 27, 2014, 11 pages.
Henderson et al., “Efficient Natural Language Response Suggestion for Smart Reply”, Available Online at: https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/1846e8a466c079eae7e90727e27caf5f98f10e0c.pdf, 2017, 15 pages.
Hershey et al., “Deep Clustering: Discriminative Embeddings for Segmentation and Separation”, Proc. ICASSP, Mar. 2016, 6 pages.
“Hey Google: How to Create a Shopping List with Your Google Assistant”, Online available at:—<https://www.youtube.com/watch?v=w9NCsElax1Y>, May 25, 2018, 1 page.
Hinton et al., “Distilling the Knowledge in a Neural Network”, arXiv preprintarXiv:1503.02531, Mar. 2, 2015, 9 pages.
“How to Enable Google Assistant on Galaxy S7 and Other Android Phones (No Root)”, Online available at:—<https://www.youtube.com/watch?v=HekIQbWyksE>, Mar. 20, 2017, 1 page.
“How to Use Ok Google Assistant Even Phone is Locked”, Online available at:—<https://www.youtube.com/watch?v=9B_gP4j_SP8>, Mar. 12, 2018, 1 page.
Hutsko et al., “iPhone All-in-One for Dummies”, 3rd Edition, 2013, 98 pages.
ID3.org, “id3v2.4.0-Frames”, Online available at:—<http://id3.org/id3v2.4.0-frames?action=print>, retrieved on Jan. 22, 2015, pp. 1-41.
Idasallinen, “What's The ‘Like’ Meter Based on?”, Online Available at: <https://community.spotify.com/t5/Content-Questions/What-s-the-like-meter-based-on/td-p/1209974>, Sep. 22, 2015, 6 pages.
Ikeda, Masaru, “beGLOBAL SEOUL 2015 Startup Battle: Talkey”, YouTube Publisher, Online Available at:—<https://www.youtube.com/watch?v=4Wkp7sAAldg>, May 14, 2015, 1 page.
Inews and Tech, “How to Use the QuickType Keyboard in IOS 8”, Online available at:—<http://www.inewsandtech.com/how-to-use-the-quicktype-keyboard-in-ios-8/>, Sep. 17, 2014, 6 pages.
Intention to Grant received for Danish Patent Application No. PA201770032, mailed on Mar. 18, 2019, 2 pages.
Intention to Grant received for Danish Patent Application No. PA201770035, mailed on Apr. 26, 2019, 2 pages.
Intention to Grant received for Danish Patent Application No. PA201770036, mailed on May 1, 2018, 2 pages.
Intention to Grant received for European Patent Application No. 19150734.2, mailed on Dec. 1, 2020, 8 pages.
Intention to Grant received for European Patent Application No. 19157463.1, mailed on Jan. 7, 2022, 17 pages.
Intention to Grant received for European Patent Application No. 19157463.1, mailed on Mar. 1, 2022, 17 pages.
“Interactive Voice”, Online available at:—<http://www.helloivee.com/company/>, retrieved on Feb. 10, 2014, 2 pages.
International Preliminary Report on Patentability received for PCT Patent Application No. PCT/US2016/059953, mailed on Dec. 20, 2018, 9 pages.
International Search Report and Written Opinion received for PCT Patent Application No. PCT/US2016/059953, mailed on Mar. 10, 2017., 13 pages.
Internet Services and Social Net, “How to Search for Similar Websites”, Online available at:—<https://www.youtube.com/watch?v=nLf2uirpt5s>, see from 0:17 to 1:06, Jul. 4, 2013, 1 page.
Invitation to Pay Additional Fees Received for PCT Patent Application No. PCT/US2016/059953, mailed on Dec. 29, 2016, 2 pages.
“iPhone 6 Smart Guide Full Version for SoftBank”, Gijutsu-Hyohron Co., Ltd., vol. 1, Dec. 1, 2014, 4 pages.
Isik et al., “Single-Channel Multi-Speaker Separation using Deep Clustering”, Interspeech 2016, Sep. 8-12, 2016, pp. 545-549.
Jeon et al., “Voice Trigger Detection from LVCSR Hypothesis Lattices Using Bidirectional Lattice Recurrent Neural Networks”, International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, Feb. 29, 2020, 5 pages. EFS Web 2.1.18.
Jeong, “Development Trend of N-Screen Service”, Journal of Broadcasting Engineering, vol. 17, No. 1, Sep. 20212 18 pages.
Jonsson et al., “Proximity-based Reminders Using Bluetooth”, 2014 IEEE International Conference on Pervasive Computing and Communications Demonstrations, 2014, pp. 151-153.
Kannan et al., “Smart Reply: Automated Response Suggestion for Email”, Available Online at: https://arxiv.org/pdf/1606.04870.pdf, Jun. 15, 2016, 10 pages.
Karn, Ujjwal, “An Intuitive Explanation of Convolutional Neural Networks”, The Data Science Blog, Aug. 11, 2016, 23 pages.
Kastrenakes, Jacob, “Siri's creators will unveil their new Al bot on Monday”, The Verge, Online available at:—<https://web.archive.org/web/20160505090418/https://www.theverge.com/2016/5/4/1159 3564/viv-labs-unveiling-monday-new-ai-from-siri-creators>, May 4, 2016, 3 pages.
Kickstarter, “Ivee Sleek: Wi-Fi Voice-Activated Assistant”, Online available at:—<https://www.kickstarter.com/projects/ivee/ivee-sleek-wi-fi-voice-activated-assistant>, retrieved on Feb. 10, 2014, pp. 1-13.
King et al., “Robust Speech Recognition Via Anchor Word Representations”, Interspeech 2017, Aug. 20-24, 2017, pp. 2471-2475.
Kondrat, Tomek, “Automation for Everyone with MacroDroid”, Online available at: https://www.xda-developers.com/automation-for-everyone-with-macrodroid/, Nov. 17, 2013, 6 pages.
Kumatani et al., “Direct Modeling of Raw Audio with DNNS For Wake Word Detection”, in 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2017, 6 pages.
Lee, Sungjin, “Structured Discriminative Model For Dialog State Tracking”, Proceedings of the SIGDIAL 2013 Conference, Aug. 22-24, 2013, pp. 442-451.
Lin, Luyuan, “An Assistive Handwashing System with Emotional Intelligence”, Using Emotional Intelligence in Cognitive Intelligent Assistant Systems, 2014, 101 pages.
“Link Your Voice to Your Devices with Voice Match, Google Assistant Help”, Online available at: <https://support.google.com/assistant/answer/9071681?co=GENIE.Platform%3DAndroid&hl=en>, Retrieved on Jul. 1, 2020, 2 pages.
Liou et al., “Autoencoder for Words”, Neurocomputing, vol. 139, Sep. 2014, pp. 84-96.
Liu et al., “Accurate Endpointing with Expected Pause Duration”, Sep. 6-10, 2015, pp. 2912-2916.
Loukides et al., “What Is the Internet of Things?”, O'Reilly Media, Inc., Online Available at: <https://www.oreilly.com/library/view/what-is-the/9781491975633/>, 2015, 31 pages.
Luo et al., “Speaker-Independent Speech Separation With Deep Attractor Network”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 26, No. 4, Apr. 2018, pp. 787-796.
Maas et al., “Combining Acoustic Embeddings and Decoding Features for End-of-Utterance Detection in Real-Time Far-Field Speech Recognition Systems”, in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE,, 2018, 5 pages.
Mallidi et al., “Device-Directed Utterance Detection”, Proc. Interspeech, Aug. 7, 2018, 4 pages.
Marketing Land, “Amazon Echo: Play music”, Online Available at:—<https://www.youtube.com/watch?v=A7V5NPbsXi4>, Apr. 27, 2015, 3 pages.
“Meet Ivee, Your Wi-Fi Voice Activated Assistant”, Availale Online at:—<http://www.helloivee.com/>, retrieved on Feb. 10, 2014, 8 pages.
Mhatre et al., “Donna Interactive Chat-bot acting as a Personal Assistant”, International Journal of Computer Applications (0975-8887), vol. 140, No. 10, Apr. 2016, 6 pages.
Mikolov et al., “Linguistic Regularities in Continuous Space Word Representations”, Proceedings of NAACL-HLT, Jun. 9-14, 2013, pp. 746-751.
Miller Chance, “Google Keyboard Updated with New Personalized Suggestions Feature”, Online available at:—<http://9to5google.com/2014/03/19/google-keyboard-updated-with-new-personalized-suggestions-feature/>, Mar. 19, 2014, 4 pages.
Minutes of Oral Proceedings received for European Patent Application No. 19157463.1, mailed on Jan. 28, 2022, 9 pages.
Minutes of the Oral Proceedings received for European Patent Application No. 19157463.1, mailed on Dec. 22, 2021, 9 pages.
Mnih et al., “Human-Level Control Through Deep Reinforcement Learning”, Nature, vol. 518, Feb. 26, 2015, pp. 529-533.
Modern Techies, “Braina-Artificial Personal Assistant for PC(like Cortana,Siri)!!!!”, Online available at: <https://www.youtube.com/watch?v=_Coo2P8ilqQ>, Feb. 24, 2017, 3 pages.
Muller et al., “Control Theoretic Models of Pointing”, ACM Transactions on Computer-Human Interaction, Aug. 2017, 36 pages.
Myers, Brad A., “Shortcutter for Palm”, Available at: <http://www.cs.cmu.edu/˜pebbles/v5/shortcutter/palm/index.html>, retrieved on Jun. 18, 2014, 10 pages.
Nakamura et al., “Study of Methods to Diminish Spoilers of Sports Match: Potential of a Novel Concept “Information Clouding””, vol. 54, No. 4, ISSN: 1882- 7764. Online available at: <https://ipsj.ixsq.nii.ac.jp/ej/index.php?active_action=repository_view_main_item_detail& page_id=13&block_id=8&item_id=91589&item_no=1>, Apr. 2013, pp. 1402-1412.
“Natural Language Interface Using Constrained Intermediate Dictionary of Results”, List of Publications Manually reviewed for the Search of U.S. Pat. No. 7,177,798, Mar. 22, 2013, 1 page.
NDTV, “Sony SmartWatch 2 Launched in India for Rs. 14,990”, available at <http://gadgets.ndtv.com/others/news/sony-smartwatch-2-launched-in-india-for-rs-14990-420319>, Sep. 18, 2013, 4 pages.
Non-Final Office Action received for U.S. Appl. No. 15/271,766, mailed on Oct. 1, 2018, 16 pages.
Non-Final Office Action received for U.S. Appl. No. 16/024,447, mailed on Feb. 28, 2020, 63 pages.
Non-Final Office Action received for U.S. Appl. No. 16/024,447, mailed on Jul. 3, 2019, 50 pages.
Non-Final Office Action received for U.S. Appl. No. 16/402,922, mailed on Oct. 18, 2019, 20 pages.
Non-Final Office Action received for U.S. Appl. No. 16/717,790, mailed on Sep. 28, 2020, 13 pages.
Norouzian et al., “Exploring Attention Mechanism for Acoustic based Classification of Speech Utterances into System-Directed and Non-System-Directed”, International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, Feb. 1, 2019, 5 pages.
Notice of Acceptance received for Australian Patent application No. 2016409890, mailed on Jul. 6, 2018, 3 pages.
Notice of Acceptance received for Australian Patent Application No. 2018241102, mailed on May 22, 2019, 3 pages.
Notice of Acceptance received for Australian Patent Application No. 2019213416, mailed on Nov. 7, 2019, 3 pages.
Notice of Acceptance received for Australian Patent Application No. 2020201030, mailed on Apr. 23, 2021, 3 pages.
Notice of Allowance received for Chinese Patent Application No. 2016800792830, mailed on Apr. 13, 2021, 2 pages.
Notice of Allowance received for Chinese Patent Application No. 201910010561.2, mailed on Feb. 25, 2021, 2 pages.
Notice of Allowance received for Chinese Patent Application No. 201910115436.8, mailed on Aug. 16, 2022, 3 pages.
Notice of Allowance received for Japanese Patent Application No. 2019-121991, mailed on Dec. 13, 2019, 4 pages.
Notice of Allowance received for Korean Patent Application No. 10-2019-7004448, mailed on Sep. 28, 2020, 3 pages.
Notice of Allowance received for U.S. Appl. No. 15/271,766, mailed on Jul. 31, 2019, 19 pages.
Notice of Allowance received for U.S. Appl. No. 16/024,447, mailed on Apr. 22, 2020, 18 pages.
Notice of Allowance received for U.S. Appl. No. 16/402,922, mailed on Jun. 22, 2020, 10 pages.
Notice of Allowance received for U.S. Appl. No. 16/717,790, mailed on Jan. 19, 2021, 11 pages.
Notice of Allowance received for U.S. Appl. No. 17/231,713, mailed on Jan. 24, 2023, 11 pages.
Office Action received for Australian Patent Application No. 2019213416, mailed on Aug. 14, 2019, 4 pages.
Office Action received for Australian Patent Application No. 2020201030, mailed on Aug. 25, 2020, 4 pages.
Office Action received for Australian Patent Application No. 2020201030, mailed on Mar. 9, 2021, 4 pages.
Office Action received for Australian Patent Application No. 2020201030, mailed on Nov. 11, 2020, 4 pages.
Office Action received for Australian Patent Application No. 2021204695, mailed on Jun. 15, 2022, 5 pages.
Office Action received for Chinese Patent Application No. 201680079283.0, mailed on Oct. 9, 2020, 22 pages.
Office Action received for Chinese Patent Application No. 201910010561.2, mailed on Jul. 1, 2020, 19 pages.
Office Action received for Chinese Patent Application No. 201910115436.8, mailed on Mar. 14, 2022, 30 pages.
Office Action received for Chinese Patent Application No. 201910115436.8, mailed on Oct. 9, 2021, 28 pages.
Office Action received for Chinese Patent Application No. 202110689193.6, mailed on Aug. 1, 2022, 18 pages.
Office Action received for Chinese Patent Application No. 202110689193.6, mailed on Mar. 16, 2022, 7 pages.
Office Action received for Chinese Patent Application No. 202110689193.6, mailed on Nov. 11, 2022, 21 pages.
Office Action received for Danish Patent Application No. PA201770032, mailed on Apr. 16, 2018, 5 pages.
Office Action received for Danish Patent Application No. PA201770032, mailed on Apr. 18, 2017., 10 pages.
Office Action received for Danish Patent Application No. PA201770032, mailed on Feb. 18, 2019, 2 pages.
Office Action received for Danish Patent Application No. PA201770032, mailed on Oct. 19, 2017., 2 pages.
Office Action received for Danish Patent Application No. PA201770035, mailed on Jan. 8, 2019, 4 pages.
Office Action received for Danish Patent Application No. PA201770035, mailed on Mar. 20, 2018, 5 pages.
Office Action received for Danish Patent Application No. PA201770035, mailed on Mar. 23, 2017., 6 pages.
Office Action received for Danish Patent Application No. PA201770035, mailed on Oct. 17, 2017., 4 pages.
Office Action received for Danish Patent Application No. PA201770036, mailed on Feb. 21, 2018., 3 pages.
Office Action received for Danish Patent Application No. PA201770036, mailed on Jun. 20, 2017., 10 pages.
Office Action received for European Patent Application No. 16904830.3, mailed on Feb. 28, 2020, 7 pages.
Office Action received for European Patent Application No. 19150734.2, mailed on Feb. 21, 2020, 7 pages.
Office Action received for European Patent Application No. 19157463.1, mailed on Mar. 2, 2020, 7 pages.
Office Action received for Japanese Patent Application No. 2018-535277, mailed on Mar. 12, 2019, 7 pages.
Office Action received for Japanese Patent Application No. 2018-535277, mailed on Nov. 19, 2018, 10 pages.
Office Action received for Japanese Patent Application No. 2019-121991, mailed on Aug. 30, 2019, 4 pages.
Office Action received for Korean Patent Application No. 10-2018-7023111, mailed on Dec. 12, 2019, 6 pages.
Office Action received for Korean Patent Application No. 10-2018-7023111, mailed on Sep. 25, 2019, 6 pages.
Office Action received for Korean Patent Application No. 10-2019-7004448, mailed on May 22, 2020, 9 pages.
Office Action received for Korean Patent Application No. 10-2019-7004448, mailed on Sep. 19, 2019, 12 pages.
Office Action received for Korean Patent Application No. 10-2020-7037709, mailed on Jan. 24, 2022, 10 pages.
Office Action received for Korean Patent Application No. 10-2020-7037709, mailed on Jan. 27, 2021, 9 pages.
Office Action received for Korean Patent Application No. 10-2020-7037709, mailed on Jul. 27, 2021, 8 pages.
Office Action received for Korean Patent Application No. 10-2020-7037709, mailed on May 25, 2022, 7 pages.
Office Action received for Korean Patent Application No. 10-2020-7037709, mailed on Nov. 18, 2022, 6 pages.
Office Action received for Korean Patent Application No. 10-2018-7023111, mailed on Jan. 2, 2019, 11 pages.
OSXDaily, “Get a List of Siri Commands Directly from Siri”, Online available at:—<http://osxdaily.com/2013/02/05/list-siri-commands/>, Feb. 5, 2013, 15 pages.
Pak, Gamerz, “Braina: Artificially Intelligent Assistant Software for Windows PC in (urdu / hindhi)”, Online available at: <https://www.youtube.com/watch?v=JH_rMjw8lqc>, Jul. 24, 2018, 3 pages.
Pathak et al., “Privacy-preserving Speech Processing: Cryptographic and String-matching Frameworks Show Promise”, In: IEEE signal processing magazine, Online available at:—<http://www.merl.com/publications/docs/TR2013-063.pdf>, Feb. 13, 2013, 16 pages.
Patra et al., “A Kernel-Based Approach for Biomedical Named Entity Recognition”, Scientific World Journal, vol. 2013, 2013, pp. 1-7.
Pavlopoulos et al., “ConvAI at SemEval-2019 Task 6: Offensive Language Identification and Categorization with Perspective and BERT”, Proceedings of the 13th International Workshop on Semantic Evaluation (SemEval-2019), Jun. 6-7, 2019, pp. 571-576.
PC MAG, “How to Voice Train Your Google Home Smart Speaker”, Online available at: <https://in.pcmag.com/google-home/126520/how-to-voice-train-your-google-home-smart-speaker>, Oct. 25, 2018, 12 pages.
Pennington et al., “GloVe: Global Vectors for Word Representation”, Proceedings of the Conference on Empirical Methods Natural Language Processing (EMNLP), Doha, Qatar, Oct. 25-29, 2014, pp. 1532-1543.
Perlow, Jason, “Alexa Loop Mode with Playlist for Sleep Noise”, Online Available at: <https://www.youtube.com/watch?v=nSkSuXziJSg>, Apr. 11, 2016, 3 pages.
Philips, Chris, “Thumbprint Radio: A Uniquely Personal Station Inspired by All of Your Thumbs Up”, Pandora News, Online Available at:—<https://blog.pandora.com/author/chris-phillips/>, Dec. 14, 2015, 7 pages.
Ping, et al., “Deep Voice 3: Scaling Text to Speech with Convolutional Sequence Learning”, Available online at: https://arxiv.org/abs/1710.07654, Feb. 22, 2018, 16 pages.
Pocketables.com, “AutoRemote example profile”, Online available at: https://www.youtube.com/watch?v=kC_zhUnNZj8, Jun. 25, 2013, 1 page.
“Pose, Cambridge Dictionary Definition of Pose”, Available online at: <https://dictionary.cambridge.org/dictionary/english/pose>, 4 pages.
Qian et al., “Single-channel Multi-talker Speech Recognition With Permutation Invariant Training”, Speech Communication, Issue 104, 2018, pp. 1-11.
“Quick Type Keyboard on iOS 8 Makes Typing Easier”, Online available at:—<https://www.youtube.com/watch?v=0CldLR4fhVU>, Jun. 3, 2014, 3 pages.
“Radio Stations Tailored to You Based on the Music You Listen to on iTunes”, Apple Announces iTunes Radio, Press Release, Jun. 10, 2013, 3 pages.
Rasch, Katharina, “Smart Assistants for Smart Homes”, Doctoral Thesis in Electronic and Computer Systems, 2013, 150 pages.
Ravi, Sujith, “Google AI Blog: On-device Machine Intelligence”, Available Online at: https://ai.googleblog.com/2017/02/on-device-machine-intelligence.html, Feb. 9, 2017, 4 pages.
Result of Consultation received for European Patent Application No. 16904830.3, mailed on Feb. 18, 2021, 4 pages.
Result of Consultation received for European Patent Application No. 19150734.2, mailed on Nov. 16, 2020, 3 pages.
Result of Consultation received for European Patent Application No. 19157463.1 mailed on Feb. 9, 2022, 3 pages.
Result of Consultation received for European Patent Application No. 19157463.1 mailed on Jan. 18, 2022, 3 pages.
Result of Consultation received for European Patent Application No. 19157463.1, mailed on Mar. 5, 2021, 7 pages.
Result of Consultation received for European Patent Application No. 19157463.1, mailed on Nov. 5, 2021, 9 pages.
Rios Mafe, “New Bar Search for Facebook”, YouTube, available at:—<https://www.youtube.com/watch?v=vwgN1WbvCas>, Jul. 19, 2013, 2 pages.
Ritchie, Rene, “QuickType keyboard in iOS 8: Explained”, Online Available at:—<https://www.imore.com/quicktype-keyboards-ios-8-explained>, Jun. 21, 2014, pp. 1-19.
Routines, “SmartThings Support”, Online available at:—<https://web.archive.org/web/20151207165701/https://support.smartthings.com/hc/en-us/articles/205380034-Routines>, 2015, 3 pages.
Rowland et al., “Designing Connected Products: UX for the Consumer Internet of Things”, O'Reilly, May 2015, 452 pages.
Samsung Support, “Create a Quick Command in Bixby to Launch Custom Settings by at Your Command”, Online Available at:—<https://www.facebook.com/samsungsupport/videos/10154746303151213>, Nov. 13, 2017, 1 page.
Santos et al., “Fighting Offensive Language on Social Media with Unsupervised Text Style Transfer”, Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (vol. 2: Short Papers), May 20, 2018, 6 pages.
Seehafer Brent, “Activate Google Assistant on Galaxy S7 with Screen off”, Online available at:—<https://productforums.google.com/forum/#!topic/websearch/lp3qIGBHLVI>, Mar. 8, 2017, 4 pages.
Selfridge et al., “Interact: Tightly-coupling Multimodal Dialog with an Interactive Virtual Assistant”, International Conference on Multimodal Interaction, ACM, Nov. 9, 2015, pp. 381-382.
Senior et al., “Improving DNN Speaker Independence With I-Vector Inputs”, ICASSP, 2014, pp. 225-229.
Seroter et al., “SOA Patterns with BizTalk Server 2013 and Microsoft Azure”, Packt Publishing, Jun. 2015, 454 pages.
Settle et al., “End-to-End Multi-Speaker Speech Recognition”, Proc. ICASSP, Apr. 2018, 6 pages.
Shen et al., “Style Transfer from Non-Parallel Text by Cross-Alignment”, 31st Conference on Neural Information Processing Systems (NIPS 2017), 2017, 12 pages.
Sigtia et al., “Efficient Voice Trigger Detection for Low Resource Hardware”, in Proc. Interspeech 2018, Sep. 2-6, 2018, pp. 2092-2096.
Sigtia et al., “Multi-Task Learning for Voice Trigger Detection”, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, Apr. 20, 2020, 5 pages.
Simonite, Tom, “Confronting Siri: Microsoft Launches Digital Assistant Cortana”, 2014, 2 pages.
Siou, Serge, “How to Control Apple TV 3rd Generation Using Remote app”, Online available at: <https://www.youtube.com/watch?v=PhyKftZ0S9M>, May 12, 2014, 3 pages.
“Skilled at Playing my iPhone 5”, Beijing Hope Electronic Press, Jan. 2013, 6 pages.
“SmartThings +Amazon Echo”, Smartthings Samsung [online], Online available at:—<https://web.archive.org/web/20160509231428/https://blog.smartthings.com/featured/alexa-turn-on-my-smartthings/>, Aug. 21, 2015, 3 pages.
Smith, Jake, “Amazon Alexa Calling: How to Set it up and Use it on Your Echo”, iGeneration, May 30, 2017, 5 pages.
Sperber et al., “Self-Attentional Models for Lattice Inputs”, in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, Association for Computational Linguistics, Jun. 4, 2019, 13 pages.
SRI, “SRI Speech: Products: Software Development Kits: EduSpeak”, Online available at: <http://web.archive.org/web/20090828084033/http://www.speechatsri.com/products/eduspeak>shtml, retrieved on Jun. 20, 2013, pp. 1-2.
Summons to Attend Oral Proceedings received for European Patent Application No. 16904830.3, mailed on Dec. 5, 2022, 3 pages.
Summons to Attend Oral Proceedings received for European Patent Application No. 16904830.3, mailed on Sep. 3, 2020, 10 pages.
Summons to Attend Oral Proceedings received for European Patent Application No. 19150734.2, mailed on Aug. 5, 2020, 9 pages.
Summons to Attend Oral Proceedings received for European Patent Application No. 19157463.1, mailed on Apr. 22, 2021, 21 pages.
Summons to Attend Oral Proceedings received for European Patent Application No. 19157463.1, mailed on Sep. 14, 2020, 10 pages.
Sundermeyer et al., “From Feedforward to Recurrent LSTM Neural Networks for Language Modeling.”, IEEE Transactions to Audio, Speech, and Language Processing, vol. 23, No. 3, Mar. 2015, pp. 517-529.
Sutskever et al., “Sequence to Sequence Learning with Neural Networks”, Proceedings of the 27th International Conference on Neural Information Processing Systems, 2014, 9 pages.
Tamar et al., “Value Iteration Networks”, Advances in Neural Information Processing Systems, vol. 29, 2016, 16 pages.
Tan et al., “Knowledge Transfer in Permutation Invariant Training for Single-channel Multi-talker Speech Recognition”, ICASSP 2018, 2018, pp. 5714-5718.
Tech Target Contributor, “AI Accelerator”, Available online at: https://searchenterpriseai.techtarget.com/definition/AI-accelerator, Apr. 2018, 3 pages.
“Use Macrodroid skillfully to automatically clock in with Ding Talk”, Online available at: https://blog.csdn.net/qq_26614295/article/details/84304541, Nov. 20, 2018, 11 pages.
Vaswani et al., “Attention Is All You Need”, 31st Conference on Neural Information Processing Systems (NIPS 2017), 2017, pp. 1-11.
Villemure et al., “The Dragon Drive Innovation Showcase: Advancing the State-of-the-art in Automotive Assistants”, 2018, 7 pages.
Walker, Amy, “NHS Gives Amazon Free Use of Health Data Under Alexa Advice Deal”, Available online at: <https://www.theguardian.com/society/2019/dec/08/nhs-gives-amazon-free-use-of-health-data-under-alexa-advice-deal>, 3 pages.
Wang et al., “End-to-end Anchored Speech Recognition”, Proc. ICASSP2019, May 12-17, 2019, 5 pages.
Wang, et al., “Tacotron: Towards End to End Speech Synthesis”, Available online at: https://arxiv.org/abs/1703.10135, Apr. 6, 2017, 10 pages.
Wang, et al., “Training Deep Neural Networks with 8-bit Floating Point Numbers”, 32nd Conference on Neural Information Processing Systems (Neurl PS 2018), 2018, 10 pages.
Weng et al., “Deep Neural Networks for Single-Channel Multi-Talker Speech Recognition”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 23, No. 10, Oct. 2015, pp. 1670-1679.
“What's on Spotify?”, Music for everyone, Online Available at:—<https://web.archive.org/web/20160428115328/https://www.spotify.com/us/>, Apr. 28, 2016, 6 pages.
Wikipedia, “Home Automation”, Online Available at:—<https://en.wikipedia.org/w/index.php?title=Home_automation&oldid=686569068>, Oct. 19, 2015, 9 pages.
Wikipedia, “Siri”, Online Available at:—<https://en.wikipedia.org/w/index.php?title=Siri&oldid=689697795>, Nov. 8, 2015, 13 Pages.
Wikipedia, “Virtual Assistant”, Wikipedia, Online Available at:—<https://en.wikipedia.org/w/index.php?title=Virtual_assistant&oldid=679330666>, Sep. 3, 2015, 4 pages.
Win, et al., “Myanmar Text to Speech System based on Tacotron-2”, International Conference on Information and Communication Tecnology Convergence (ICTC), Oct. 21-23, 2020, pp. 578-583.
Wu et al., “Monophone-Based Background Modeling for Two-Stage on-device Wake Word Detection”, in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr. 2018, 5 pages.
X.AI, “How it Works”, Online available at:—<https://web.archive.org/web/20160531201426/https://x.ai/how-it-works/>, May 31, 2016, 6 pages.
Xiang et al., “Correcting Phoneme Recognition Errors in Learning Word Pronunciation through Speech Interaction”, Speech Communication, vol. 55, No. 1, Jan. 1, 2013, pp. 190-203.
Xu et al., “Policy Optimization of Dialogue Management in Spoken Dialogue System for Out-of-Domain Utterances”, 2016 International Conference on Asian Language Processing (IALP), IEEE, Nov. 21, 2016, pp. 10-13.
Xu et al., “Show, Attend and Tell: Neural Image Caption Generation with Visual Attention”, Proceedings of the 32nd International Conference on Machine Learning, Lille, France, 2015, 10 pages.
Yan et al., “A Scalable Approach to Using DNN-derived Features in GMM-HMM Based Acoustic Modeling for LVCSR”, 14th Annual Conference of the International Speech Communication Association, InterSpeech 2013, Aug. 2013, pp. 104-108.
Yang Astor, “Control Android TV via Mobile Phone APP RKRemoteControl”, Online Available at : <https://www.youtube.com/watch?v=zpmUeOX_xro>, Mar. 31, 2015, 4 pages.
Yates Michaelc., “How Can I Exit Google Assistant After I'm Finished with it”, Online available at:—<https://productforums.google.com/forum/#!msg/phone-by-google/faECnR2RJwA/gKNtOkQgAQAJ>, Jan. 11, 2016, 2 pages.
Yeh Jui-Feng, “Speech Act Identification Using Semantic Dependency Graphs With Probabilistic Context-free Grammars”, ACM Transactions on Asian and Low-Resource Language Information Processing, vol. 15, No. 1, Dec. 2015, pp. 5.1-5.28.
Young et al., “POMDP-Based Statistical Spoken Dialog Systems: A Review”, Proceedings of the IEEE, vol. 101, No. 5, 2013, 18 pages.
Yousef, Zulfikara., “Braina (A.I) Artificial Intelligence Virtual Personal Assistant”, Online available at:—<https://www.youtube.com/watch?v=2h6xpB8bPSA>, Feb. 7, 2017, 3 pages.
Yu et al., “Permutation Invariant Training of Deep Models for Speaker-Independent Multi-talker Speech Separation”, Proc. ICASSP, 2017, 5 pages.
Yu et al., “Recognizing Multi-talker Speech with Permutation Invariant Training”, Interspeech 2017, Aug. 20-24, 2017, pp. 2456-2460.
Zhang et al., “Very Deep Convolutional Networks for End-To-End Speech Recognition”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017, 5 pages.
Zheng, et al., “Intent Detection and Semantic Parsing for Navigation Dialogue Language Processing”, 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), 2017, 6 pages.
Zhong et al., “JustSpeak: Enabling Universal Voice Control on Android”, W4A'14, Proceedings of the 11th Web for All Conference, No. 36, Apr. 7-9, 2014, 8 pages.
Zhou et al., “Learning Dense Correspondence via 3D-guided Cycle Consistency”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, 10 pages.
Zmolikova et al., “Speaker-Aware Neural Network Based Beamformer for Speaker Extraction in Speech Mixtures”, Interspeech 2017, Aug. 20-24, 2017, pp. 2655-2659.
Office Action received for Chinese Patent Application No. 202110024848.8, mailed on Feb. 29, 2024, 16 pages (9 pages of English Translation and 7 pages of Official Copy).
Office Action received for Korean Patent Application No. 10-2023-7000495, mailed on Apr. 29, 2024, 7 pages (3 pages of English Translation and 4 pages of Official Copy).
Extended European Search Report received for European Patent Application No. 23191700.6, mailed on Nov. 3, 2023, 7 pages.
Communication of Board of Appeal received for European Patent Application No. 16904830.3, mailed on May 25, 2023, 8 pages.
Office Action received for Korean Patent Application No. 10-2023-7000495, mailed on Jul. 28, 2023, 13 pages (6 pages of English Translation and 7 pages of Official Copy).
Office Action received for Korean Patent Application No. 10-2023-7000495, mailed on Dec. 28, 2023, 7 pages (3 pages of English Translation and 4 pages of Official Copy).
Abdelaziz et al., “Speaker-Independent Speech-Driven Visual Speech Synthesis using Domain-Adapted Acoustic Models”, May 15, 2019, 9 pages.
Accessibility on iOS, Apple Inc., Online available at: https://developer.apple.com/accessibility/ios/, Retrieved on Jul. 26, 2021, 2 pages.
Apple, “Apple previews innovative accessibility features combining the power of hardware, software, and machine learning”, Available online at: https://www.apple.com/newsroom/2022/05/apple-previews-innovative-accessibility-features/, May 17, 2022, 10 pages.
Badshah, et al., “Deep Features-based Speech Emotion Recognition For Smart Affective Services”, Multimedia Tools and Applications, Oct. 31, 2017, pp. 5571-5589.
Büttner et al., “The Design Space of Augmented and Virtual Reality Applications for Assistive Environments in Manufacturing: A Visual Approach”, In Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '17), Island of Rhodes, Greece, Online available at: https://dl.acm.org/doi/pdf/10.1145/3056540.3076193, Jun. 21-23, 2017, pp. 433-440.
“Cake”, Online Available at: <https://web.archive.org/web/20170808091948/https://emojipedia.org/search/?q=cake>, Aug. 8, 2017, 5 pages.
Castellini, Rick, “How to enable and use dictation with an iPhone or iPad”, Online Available at: <https://www.youtube.com/watch?v=8w133yN6rTU>, Sep. 7, 2017, 3 pages.
“Context-Sensitive User Interface” , Online available at: https://web.archive.org/web/20190407003349/https://en.wikipedia.org/wiki/Context-sensitive_user_interface, Apr. 7, 2019, 3 pages.
Creswell et al., “Generative Adversarial Networks”, IEEE Signal Processing Magazine, Jan. 2018, pp. 53-65.
Fitzpatrick, Aidan, “Introducing Camo 1.5: AR modes”, Available Online at : “https://reincubate.com/blog/camo-ar-modes-release/”, Oct. 28, 2021, 8 pages.
Ganin et al., “Unsupervised Domain Adaptation by Backpropagation”, in Proceedings of the 32nd International Conference on Machine Learning, vol. 37, Jul. 2015, 10 pages.
Geyer et al., “Differentially Private Federated Learning: A Client Level Perspective”, arXiv:1712.07557v2, Mar. 2018, 7 pages.
Gomes et al., “Mining Recurring Concepts in a Dynamic Feature Space”, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, No. 1, Jul. 31, 2013, pp. 95-110.
Guo et al., “StateLens: A Reverse Engineering Solution for Making Existing Dynamic Touchscreens Accessible”, In Proceedings of the 32nd Annual Symposium on User Interface Software and Technology (UIST '19), New Orleans, LA, USA, Online available at: https://dl.acm.org/doi/pdf/10.1145/3332165.3347873, Oct. 20-23, 2019, pp. 371-385.
Guo et al., “VizLens: A Robust and Interactive Screen Reader for Interfaces in the Real World”, In Proceedings of the 29th Annual Symposium on User Interface Software and Technology (UIST '16), Tokyo, Japan, Online available at: https://dl.acm.org/doi/pdf/10.1145/2984511.2984518, Oct. 16-19, 2016, pp. 651-664.
Hanqing et al., “Deep Learning of Instruction Intention Understanding Using Stacked Denoising Autoencoder”, Journal of Shanghai Jiaotong University, vol. 50 No. 7, Jul. 28, 2016, 6 pages (Official Copy only). {See communication under 37 CFR § 1.98(a) (3)}.
Hawkeye, “Hawkeye—A better user testing platform”, Online Available at: https://www.youtube.com/watch?v=el0TW0g_760, Oct. 16, 2019, 3 pages.
Hawkeye, “Learn where people look in your products”, Online Available at: https://www.usehawkeye.com, 2019, 6 pages.
Heller et al., “AudioScope: Smartphones as Directional Microphones in Mobile Audio Augmented Reality Systems”, In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15), Crossings, Seoul, Korea, Online available at: https://dl.acm.org/doi/pdf/10.1145/2702123.2702159, Apr. 18-23, 2015, pp. 949-952.
Hook et al., “Automatic speech based emotion recognition using paralinguistics features”, Bulletin of the Polish Academy of Sciences, Technical Sciences, vol. 67, No. 3, 2019, pp. 479-488.
“How to adjust the order of control center buttons on iPhone iOS12 version after buying a mobile phone”, Available online at: https://jingyan.baidu.com/article/5bbb5albbe5a9713eba1791b.html?, Jun. 14, 2019, 4 pages (Official Copy only). {See communication under 37 CFR § 1.98(a) (3)}.
Kruger et al., “Virtual World Accessibility with the Perspective Viewer”, Proceedings of ICEAPVI, Athens, Greece, Feb. 12-14, 2015, 6 pages.
Kumar, Shiu, “Ubiquitous Smart Home System Using Android Application”, International Journal of Computer Networks & Communications (IJCNC) vol. 6, No. 1, Jan. 2014, pp. 33-43.
Lal et al., “User-Realistic Path Synthesis Via Multi-Task Generative Adversarial Networks for Continuous Path Keyboard Input”, Apple Invention Disclosure P38856, Apr. 2018.
Li et al., “Deep neural network for short-text sentiment classification”, International Conference on Database Systems for Advanced Applications, Springer, Cham, 2016, 8 pages.
“Method to Provide Remote Voice Navigation Capability on the Device”, ip.com, Jul. 21, 2016, 4 pages.
Michalevsky et al., “Gyrophone: Recognizing Speech from Gyroscope Signals”, Proceedings of the 23rd USENIX Security Symposium, Aug. 20-22, 2014, pp. 1053-1067.
Microsoft Soundscape—A map delivered in 3D sound, Microsoft Research, Online available at: https://www.microsoft.com/en-us/research/product/soundscape/, Retrieved on Jul. 26, 2021, 5 pages.
Müller et al., “A Taxonomy for Information Linking in Augmented Reality”, AVR 2016, Part I, LNCS 9768, 2016, pp. 368-387.
Myrick et al., “How to Insert Emojis Using Your Voice with Google Assistant”, Online available at: <https://web.archive.org/web/20211107160722/https://www.androidcentral.com/how-insert-emojis-using-your-voice-google-assistant>, Nov. 7, 2021, 11 pages.
“Nuance Dragon Naturally Speaking”, Version 13 End-User Workbook, Nuance Communications Inc., Sep. 2014, 125 pages.
Products for Pals—ALS Tech, “Skyle for iPad Pro eye gaze control real world review”, Online Available at: <https://www.youtube.com/watch?v =_3TxZtDJpFo>, Aug. 13, 2020, 4 pages.
Raux, Antoine, “High-Density Dialog Management The Topic Stack”, Adventures in High Density, Online available at: https://medium.com/adventures-in-high-density/high-density-dialog-management-23efcf91db1e, Aug. 1, 2018, 10 pages.
Robbins, F Mike, “Automatically place an Android Phone on Vibrate at Work”, Available online at: https://mikefrobbins.com/2016/07/21/automatically-place-an-android-phone-on-vibrate-at-work/, Jul. 21, 2016, pp. 1-11.
Rodrigues et al., “Exploring Mixed Reality in Specialized Surgical Environments”, In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems (Chi Ea '17), Denver, CO, USA, Online available at: https://dl.acm.org/doi/pdf/10.1145/3027063.3053273, May 6-11, 2017, pp. 2591-2598.
Ross et al., “Epidemiology as a Framework for Large-Scale Mobile Application Accessibility Assessment”, In Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '17), Baltimore, MD, USA, Online available at: https://dl.acm.org/doi/pdf/10.1145/3132525.3132547, Oct. 29-Nov. 1, 2017, pp. 2-11.
Schenk et al., “GazeEverywhere: Enabling Gaze-only User Interaction on an Unmodified Desktop PC in Everyday Scenarios”, In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI'17). ACM, New York, NY, 30343044. Online Available at: https://doi.org/10.1145/3025453.3025455, May 6-11, 2017, 11 pages.
Speicher et al., “What is Mixed Reality?”, In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). ACM, Article 537, Glasgow, Scotland, UK, Online available at: https://dl.acm.org/doi/pdf/10.1145/3290605.3300767, May 4-9, 2019, 15 pages.
Tech With Brett, “Everything the Google Nest Hub Can Do”, Available online at: https://www.youtube.com/watch?v=x3vdytgru2E, Nov. 12, 2018, 13 pages.
Tech With Brett, “Google Home Multiple Users Setup”, Available online at: https://www.youtube.com/watch?v=BQOAbRUeFRo&t=257s, Jun. 29, 2017, 4 pages.
Tkachenko, Sergey, “Chrome will automatically create Tab Groups”, Available online at : https://winaero.com/chrome-will-automatically-create-tab-groups/, Sep. 18, 2020, 5 pages.
Tkachenko, Sergey, “Enable Tab Groups Auto Create in Google Chrome”, Available online at : https://winaero.com/enable-tab-groups-auto-create-in-google-chrome/, Nov. 30, 2020, 5 pages.
Vazquez et al., “An Assisted Photography Framework to Help Visually Impaired Users Properly Aim a Camera”, ACM Transactions on Computer-Human Interaction, vol. 21, No. 5, Article 25, Online available at: https://dl.acm.org/doi/pdf/10.1145/2651380, Nov. 2014, 29 pages.
Velian Speaks Tech, “10 Google Assistant Tips!”, Available online at: https://www.youtube.com/watch?v=3RNWA3NK9fs, Feb. 24, 2020, 3 pages.
Wei et al., “Design and Implement on Smart Home System”, 2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications, Available online at: https://ieeexplore.ieee.org/document/6843433, 2013, pp. 229-231.
“Working with the Dragon Bar”, Nuance Communications, Inc, Jun. 27, 2016, 2 pages.
Zhang et al., “Interaction Proxies for Runtime Repair and Enhancement of Mobile Application Accessibility”, In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17). ACM, Denver, CO, USA, Online available at: https://dl.acm.org/doi/pdf/10.1145/3025453.3025846, May 6-11, 2017, pp. 6024-6037.
Zhao et al., “Big Data Analysis and Application”, Aviation Industry Press, Dec. 2015, pp. 236-241 (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}.
Zhao et al., “CueSee: Exploring Visual Cues for People with Low Vision to Facilitate a Visual Search Task”, In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, UbiComp '16, Heidelberg, Germany, Online available at: https://dl.acm.org/doi/pdf/10.1145/2971648.2971730, Sep. 12-16, 2016, pp. 73-84.
Zhao et al., “Enabling People with Visual Impairments to Navigate Virtual Reality with a Haptic and Auditory Cane Simulation”, In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, Article 116, Montréal, QC, Canada, Online available at: https://dl.acm.org/doi/pdf/10.1145/3173574.3173690, Apr. 21-26, 2018, 14 pages.
Zhao et al., “SeeingVR: A Set of Tools to Make Virtual Reality More Accessible to People with Low Vision”, In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). ACM, Article 111, Glasgow, Scotland, UK, Online available at: https://dl.acm.org/doi/pdf/10.1145/3290605.3300341, May 4-9, 2019, 14 pages.
Zhao et al., “Transferring Age and Gender Attributes for Dimensional Emotion Prediction from Big Speech Data Using Hierarchical Deep Learning”, 2018 4th IEEE International Conference on Big Data Security on Cloud, 2018, pp. 20-24.
Zhang et al., “A Fiber-Optic Sensor for Acoustic Emission Detection in a High Voltage Cable System”, Online Available at: https://www.mdpi.com/1424-8220/16/12/2026, Nov. 30, 2016, 11 pages.
Zhang et al., “Compact Acoustic Modeling Based on Acoustic Manifold Using a Mixture of Factor Analyzers”, Workshop on Automatic Speech Recognition and Understanding, 2013, 6 pages.
Zhang et al., “IEHouse: A Non-Intrusive Household Appliance State Recognition System”, IEEE Smart World, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, 2017, 8 pages.
Zhang et al., “Voicemoji: Emoji Entry Using Voice for Visually Impaired People”, CHI '21, May 8-13, 2021, 18 pages.
Office Action received for Chinese Patent Application No. 202110689197.4, mailed on Sep. 19, 2024, 14 pages (8 pages of English Translation and 6 pages of Official Copy).
Related Publications (1)
Number Date Country
20230352016 A1 Nov 2023 US
Provisional Applications (1)
Number Date Country
62348728 Jun 2016 US
Continuations (3)
Number Date Country
Parent 17231713 Apr 2021 US
Child 18136710 US
Parent 16717790 Dec 2019 US
Child 17231713 US
Parent 15271766 Sep 2016 US
Child 16717790 US