Patent Grant
10956666
The present disclosure relates generally to a virtual assistant, and more specifically to techniques for interacting with a virtual assistant.
Intelligent automated assistants (or digital assistants) provide a beneficial interface between human users and electronic devices. Such assistants allow users to interact with devices or systems using natural language in spoken and/or text forms. For example, a user can access the services of an electronic device by providing a spoken user request to a digital assistant associated with the electronic device. The digital assistant can interpret the user's intent from the spoken user request and operationalize the user's intent into tasks. The tasks can then be performed by executing one or more services of the electronic device and a relevant output can be returned to the user in natural language form or displayed on a device screen.
A digital assistant can be helpful in remembering calendar events or other reminders that have been set specifically by a user. A digital assistant also can be helpful in generating a recommendation based on a user request and on third-party reviews that are publicly available. However, digital assistants generally have not been useful in handling unconventional interactions, such as interactions with users other than a primary user, interactions with other virtual assistants, complex interactions, and interactions with physical entities. Further, digital assistants generally have not been useful in performing tasks that are spread out in time, or that include contingent steps or encounter exceptions.
Some techniques for interacting with a virtual assistant, however, may be cumbersome and inefficient. For example, existing techniques use a complex and time-consuming user interface, which may include multiple key presses or keystrokes. Such a user interface may be impractical or impossible in certain circumstances, such as when the user is operating a motor vehicle or has his or her hands full. Existing techniques require more time than necessary, wasting user time and device energy. For example, existing techniques may require a number of separate interactions with the user in order to fulfill a user request. This consideration is particularly important in battery-operated devices.
Accordingly, there is a need for electronic devices with faster, more efficient methods and interfaces for interacting with a virtual assistant. Such methods and interfaces optionally complement or replace other methods for interacting with a virtual assistant. Such methods and interfaces reduce the cognitive burden on a user and produce a more efficient human-machine interface. For battery-operated computing devices, such methods and interfaces conserve power and increase the time between battery charges.
In some embodiments, a non-transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to receive an unstructured natural-language user request for a service from a virtual assistant; determine whether the user request corresponds to at least one of a plurality of plan templates accessible to the virtual assistant, based on the content of the user request and the content of the plan templates; in accordance with a determination that the user request corresponds to at least one of the plurality of plan templates, select one of the plurality of plan templates; and in accordance with a determination that the user request fails to correspond to at least one of the plurality of plan templates, forego selection of a plan template; and in response to selection of one of the plan templates, begin to respond to the user request according to the selected plan template.
In some embodiments, a transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to receive an unstructured natural-language user request for a service from a virtual assistant; determine whether the user request corresponds to at least one of a plurality of plan templates accessible to the virtual assistant, based on the content of the user request and the content of the plan templates; in accordance with a determination that the user request corresponds to at least one of the plurality of plan templates, select one of the plurality of plan templates; and in accordance with a determination that the user request fails to correspond to at least one of the plurality of plan templates, forego selection of a plan template; and in response to selection of one of the plan templates, begin to respond to the user request according to the selected plan template.
In some embodiments, an electronic device includes a memory; a microphone; and a processor coupled to the memory and the microphone, the processor configured to receive an unstructured natural-language user request for a service from a virtual assistant; determine whether the user request corresponds to at least one of a plurality of plan templates accessible to the virtual assistant, based on the content of the user request and the content of the plan templates; in accordance with a determination that the user request corresponds to at least one of the plurality of plan templates, select one of the plurality of plan templates; and in accordance with a determination the user request fails to correspond to at least one of the plurality of plan templates, forego selection of a plan template; and in response to selection of one of the plan templates, begin to respond to the user request according to the selected plan template.
In some embodiments, a method of using a virtual assistant includes, at an electronic device configured to transmit and receive data, receiving an unstructured natural-language user request for a service from a virtual assistant; determining whether the user request corresponds to at least one of a plurality of plan templates accessible to the virtual assistant, based on the content of the user request and the content of the plan templates; in accordance with a determination that the user request corresponds to at least one of the plurality of plan templates, selecting one of the plurality of plan templates; and in accordance with a determination the user request fails to correspond to at least one of the plurality of plan templates, foregoing selection of a plan template; and in response to selection of one of the plan templates, beginning to respond to the user request according to the selected plan template.
In some embodiments, a system utilizes an electronic device, the system including means for receiving an unstructured natural-language user request for a service from a virtual assistant; means for determining whether the user request corresponds to at least one of a plurality of plan templates accessible to the virtual assistant, based on the content of the user request and the content of the plan templates; in accordance with a determination that the user request corresponds to at least one of the plurality of plan templates, means for selecting one of the plurality of plan templates; and in accordance with a determination the user request fails to correspond to at least one of the plurality of plan templates, means for foregoing selection of a plan template; and in response to selection of one of the plan templates, means for beginning to respond to the user request according to the selected plan template.
In some embodiments, an electronic device includes a processing unit that includes a receiving unit, a determining unit, a selecting unit, and a responding unit; the processing unit configured to receive, using the receiving unit, an unstructured natural-language user request for a service from a virtual assistant; determine, using the determining unit, whether the user request corresponds to at least one of a plurality of plan templates accessible to the virtual assistant, based on the content of the user request and the content of the plan templates; in accordance with a determination that the user request corresponds to at least one of the plurality of plan templates, select, using the selecting unit, one of the plurality of plan templates; and in accordance with a determination that the user request fails to correspond to at least one of the plurality of plan templates, forego selection, using the selecting unit, of a plan template; and in response to selection of one of the plan templates, begin to respond, using the responding unit, to the user request according to the selected plan template.
In some embodiments, a non-transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to receive from a virtual assistant a message associated with an action; store the message; and communicate the message to a second electronic device associated with the action.
In some embodiments, a transitory computer-readable storage medium stores one or more programs, the one or more programs including instructions, which when executed by an electronic device, cause the electronic device to receive from a virtual assistant a message associated with an action; store the message; and communicate the message to a second electronic device associated with the action.
In some embodiments, an electronic device includes a memory and a processor coupled to the memory, the processor configured to receive from a virtual assistant a message associated with an action; store the message; and communicate the message to a second electronic device associated with the action.
In some embodiments, a method of using a virtual assistant includes, at an electronic device configured to transmit and receive data, receiving from a virtual assistant a message associated with an action; storing the message; and communicating the message to a second electronic device associated with the action.
In some embodiments, a system utilizes an electronic device, the system including means for receiving from a virtual assistant a message associated with an action; means for storing the message; and means for communicating the message to a second electronic device associated with the action.
In some embodiments, an electronic device includes a processing unit that includes a receiving unit, a storing unit, and a communicating unit; the processing unit configured to receive, using the receiving unit, from a virtual assistant a message associated with an action; store, using the storing unit, the message; and communicate, using the communicating unit, the message to a second electronic device associated with the action.
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.
Thus, devices are provided with faster, more efficient methods and interfaces for interacting with a virtual assistant, thereby increasing the effectiveness, efficiency, and user satisfaction with such devices. Such methods and interfaces may complement or replace other methods for interacting with a virtual assistant.
For a better understanding of the various described embodiments, reference should be made to the Description of Embodiments below, in conjunction with the following drawings in which like reference numerals refer to corresponding parts throughout the figures.
The following description sets forth exemplary methods, parameters, and the like. It should be recognized, however, that such description is not intended as a limitation on the scope of the present disclosure but is instead provided as a description of exemplary embodiments.
There is a need for electronic devices that provide efficient methods and interfaces for interacting with a virtual assistant. Such methods and interfaces can reduce the cognitive burden on a user who utilizes a digital assistant to remember user data and generate recommendations, thereby enhancing productivity. Further, such techniques can reduce processor and battery power otherwise wasted on redundant user inputs.
Below,
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 touch could be termed a second touch, and, similarly, a second touch could be termed a first touch, without departing from the scope of the various described embodiments. The first touch and the second touch are both touches, but they are not the same touch.
The terminology used in the description of the various described embodiments herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used in the description of the various described embodiments 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.
Embodiments of electronic devices, user interfaces for such devices, and associated processes for using such devices are described. In some embodiments, the device is a portable communications device, such as a mobile telephone, that also contains other functions, such as PDA and/or music player functions. Exemplary embodiments of portable multifunction devices include, without limitation, the iPhone®, iPod Touch®, and iPad® devices from Apple Inc. of Cupertino, Calif. Other portable electronic devices, such as laptops or tablet computers with touch-sensitive surfaces (e.g., touch screen displays and/or touchpads), or wrist wearable devices such as the Apple Watch® wrist wearable device of Apple Inc. of Cupertino, Calif., are, optionally, used. It should also be understood that, in some embodiments, the device is not a portable communications device, but is a desktop computer with a touch-sensitive surface (e.g., a touch screen display and/or a touchpad).
In the discussion that follows, an electronic device that includes a display and a touch-sensitive surface is described. It should be understood, however, that the electronic device optionally includes one or more other physical user-interface devices, such as a physical keyboard, a mouse, and/or a joystick.
The device may support a variety of applications, such as one or more of the following: a drawing application, a presentation application, a word processing application, a website creation application, a disk authoring application, a spreadsheet application, a gaming application, a telephone application, a video conferencing application, an e-mail application, an instant messaging application, a workout support application, a photo management application, a digital camera application, a digital video camera application, a web browsing application, a digital music player application, and/or a digital video player application.
The various applications that are executed on the device optionally use at least one common physical user-interface device, such as the touch-sensitive surface. One or more functions of the touch-sensitive surface as well as corresponding information displayed on the device are, optionally, adjusted and/or varied from one application to the next and/or within a respective application. In this way, a common physical architecture (such as the touch-sensitive surface) of the device optionally supports the variety of applications with user interfaces that are intuitive and transparent to the user.
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
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
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
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
Although the digital assistant shown in
2. Electronic Devices
Attention is now directed toward embodiments of electronic devices for implementing the client-side portion of a digital assistant.
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
Memory 202 optionally can include one or more computer-readable storage mediums. The computer-readable storage mediums optionally can be tangible and non-transitory. Memory 202 optionally can include high-speed random access memory and optionally also can 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 optionally can 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 900, 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 900, 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 optionally can be implemented on a single chip, such as chip 204. In some other embodiments, they optionally can 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 optionally can 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,
I/O subsystem 206 couples input/output peripherals on device 200, such as touch display 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,
A quick press of the push button optionally can disengage a lock of touch display 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) optionally can turn power to device 200 on or off. The user optionally can be able to customize a functionality of one or more of the buttons. Touch display 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 display 212. Touch display 212 displays visual output to the user. The visual output optionally can include graphics, text, icons, video, and any combination thereof (collectively termed “graphics”). In some embodiments, some or all of the visual output optionally can correspond to user-interface objects.
Touch display 212 has a touch-sensitive surface, sensor, or set of sensors that accepts input from the user based on haptic and/or tactile contact. Touch display 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 display 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 display 212. In an exemplary embodiment, a point of contact between touch display 212 and the user corresponds to a finger of the user.
Touch display 212 optionally can use LCD (liquid crystal display) technology, LPD (light emitting polymer display) technology, or LED (light emitting diode) technology, although other display technologies optionally can be used in other embodiments. Touch display 212 and display controller 256 optionally can 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 display 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, Calif.
A touch-sensitive display in some embodiments of touch display 212 optionally can 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 display 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 display 212 optionally can 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 display 212 optionally can 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 optionally can make contact with touch display 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 optionally can 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 optionally can be a touch-sensitive surface that is separate from touch display 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 optionally can include a power management system, one or more power sources (e.g., battery, 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 (LED)) and any other components associated with the generation, management and distribution of power in portable devices.
Device 200 optionally also can include one or more optical sensors 264.
Device 200 optionally also includes one or more contact intensity sensors 265.
Device 200 optionally also can include one or more proximity sensors 266.
Device 200 optionally also includes one or more tactile output generators 267.
Device 200 optionally also can include one or more accelerometers 268.
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 (
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 display 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 display 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 optionally can be a component of graphics module 232, provides soft keyboards for entering text in various applications (e.g., contacts 237, e mail 240, IM 241, browser 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 238 for use in location-based dialing; to camera 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
Applications 236 optionally can include the following modules (or sets of instructions), or a subset or superset thereof:
Examples of other applications 236 that optionally can 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 display 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, contacts module 237 optionally can 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), e-mail 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 e-mail addresses to initiate and/or facilitate communications by telephone 238, video conference module 239, e-mail 240, or IM 241; and so forth.
In conjunction with RF circuitry 208, audio circuitry 210, speaker 211, microphone 213, touch display 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, telephone module 238 optionally can 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 optionally can 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 display 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 display 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, e-mail client module 240 includes executable instructions to create, send, receive, and manage e-mail in response to user instructions. In conjunction with image management module 244, e-mail client module 240 makes it very easy to create and send e-mails with still or video images taken with camera module 243.
In conjunction with RF circuitry 208, touch display 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, the 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 optionally can 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 display 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 display 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 display 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 display 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 display 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, e-mail 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 display 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 optionally can 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 display 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, and browser module 247, the widget creator module 250 optionally can 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 display 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 display 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 display 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 display 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 display 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 optionally can 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 display 212, display controller 256, contact/motion module 230, graphics module 232, audio circuitry 210, speaker 211, RF circuitry 208, text input module 234, e-mail 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 e-mail 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 e-mail 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 optionally can be combined or otherwise rearranged in various embodiments. For example, video player module optionally can be combined with music player module into a single module (e.g., video and music player module 252,
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 optionally can 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.
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 optionally can 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 optionally can be called the hit view, and the set of events that are recognized as proper inputs optionally can 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 optionally can 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 optionally can 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 optionally can 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 optionally can 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.
Device 200 optionally also can include one or more physical buttons, such as “home” or menu button 304. As described previously, menu button 304 optionally can be used to navigate to any application 236 in a set of applications that optionally can be executed on device 200. Alternatively, in some embodiments, the menu button is implemented as a soft key in a GUI displayed on touch display 212.
In one embodiment, device 200 includes touch display 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 display 212 and/or one or more tactile output generators 267 for generating tactile outputs for a user of device 200.
Each of the above-identified elements in
Attention is now directed towards embodiments of user interfaces that optionally can be implemented on, for example, portable multifunction device 200.
Signal strength indicator(s) 502 for wireless communication(s), such as cellular and Wi-Fi signals;
It should be noted that the icon labels illustrated in
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
Additionally, while the following examples are given primarily with reference to finger inputs (e.g., finger contacts, finger tap gestures, 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.
Techniques for detecting and processing touch intensity can 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 optionally can permit device 600 to be worn by a user.
Input mechanism 608 optionally can 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 900 (
As used here, the term “affordance” refers to a user-interactive graphical user interface object that optionally can be displayed on the display screen of devices 200, 400, and/or 600 (
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
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 optionally can 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 optionally can 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 optionally can 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 optionally can 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 optionally can 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
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 processes 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
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) 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 900, described below. One or more processors 704 can execute these programs, modules, and instructions, and reads/writes 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
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.
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
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 optionally can include the word “tomato” that is associated with the candidate pronunciations of // and /
/. 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 // can be ranked higher than /
/, 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 /
/ can be associated with the United States, whereas the candidate pronunciation /
/ 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 /
/ (associated with the United States) can be ranked higher than the candidate pronunciation /
/ (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 // 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 an utterance. Thus, for example, the STT processing module 730 can determine that the sequence of phonemes // corresponds to the word “tomato,” even if that particular sequence of phonemes is not one of the candidate sequence of phonemes for that word.
In some examples, natural language processing module 732 can be configured to receive metadata associated with the speech input. The metadata can indicate whether to perform natural language processing on the speech input (or the sequence of words or tokens corresponding to the speech input). If the metadata indicates that natural language processing is to be performed, then the natural language processing module can receive the sequence of words or tokens from the STT processing module to perform natural language processing. However, if the metadata indicates that natural language process is not to be performed, then the natural language processing module can be disabled and the sequence of words or tokens (e.g., text string) from the STT processing module can be outputted from the digital assistant. In some examples, the metadata can further identify one or more domains corresponding to the user request. Based on the one or more domains, the natural language processor can disable domains in ontology 760 other than the one or more domains. In this way, natural language processing is constrained to the one or more domains in ontology 760. In particular, the structure query (described below) can be generated using the one or more domains and not the other domains in the ontology.
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
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
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
While
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
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 optionally can 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 utterance contains insufficient information to complete the structured query associated with the domain. Therefore, other necessary parameters such as {Party Size} and {Date} optionally cannot 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 optionally can need to initiate additional dialogue with the user in order to obtain additional information, and/or disambiguate potentially ambiguous utterances. 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 receives 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 receives 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=Mar. 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.
Referring to
The user digital assistant 700a is separate from the hub digital assistant 700b; the two digital assistants 700a, 700b are discrete entities. Each separate digital assistant 700a, 700b is associated with the same user, according to some embodiments; for example, the user digital assistant 700a may be accessed by the user through his or her portable electronic device 700a, and the hub digital assistant 700b may be accessed by the user through his or her home automation system. According to other embodiments, the different digital assistants 700a, 700b are associated with different users. For example, the first digital assistant 700a may be associated with a portable electronic device 200 owned by a first user, and the second digital assistant 700b may be associated with a portable electronic device 200 owned by a second user.
Intermediation between two discrete digital assistants 700a, 700b is performed by a message gateway 770, blackboard 772, and a dispatcher 776, according to some embodiments. According to some embodiments, at least one of the gateway 770, blackboard 772, and dispatcher 776 is included within the first digital assistant 770a or the second digital assistant 770a. According to other embodiments, at least one of the gateway 770, blackboard 772, and dispatcher 776 is separate from both the first digital assistant 700a and second digital assistant 700b, and is accessible by the DA server 106 associated with at least one of the digital assistants 700a, 700b. According to other embodiments, at least one of the gateway 700, blackboard 772 and dispatcher 776 is separate from both the first digital assistant 700a and second digital assistant 700b, and is accessible by the DA client 102 associated with at least one of the digital assistants 700a, 700b.
According to some embodiments, the first digital assistant 700a is configured to transmit one or more messages to, and receive one or more messages from, the message gateway 770. The messages may be SMS messages, messages utilizing the iMessage® software feature of Apple Inc., of Cupertino, Calif., or any other suitable message format. According to other embodiments, the first digital assistant 700a instead, or additionally, is configured to transmit one or more messages to, and receive one or more messages from, the blackboard 772.
According to some embodiments, the second digital assistant 700b is configured to transmit one or more messages to, and receive one or more messages from, the blackboard 772. The messages may be SMS messages, messages utilizing the iMessage® software feature of Apple Inc., of Cupertino, Calif., or any other suitable message format. According to other embodiments, the second digital assistant 700a instead, or additionally, is configured to transmit one or more messages to, and receive one or more messages from, the message gateway 770. The blackboard 772 provides for a loosely-coupled integration between different digital assistants 700, between one or more digital assistants 700 and the dispatcher 776, and/or between one or more digital assistants 700 and one or more sensors and/or actuators directly. When one of the components of the architecture 766 needs to communicate, it generates a message and transmits that message to the blackboard 772, where it is stored. The process of generating a message and transmitting it to the blackboard 772 where it is stored may be referred to as “posting” a message to the blackboard 772. Later, one or more of the components of the architecture 766 can retrieve that message from the blackboard 772, regardless of its origin. For example, where the message includes one or more actions, the dispatcher 776 checks the blackboard 772 for messages associated with one or more actions that can be performed by sensors and/or actuators associated with the dispatcher 776; when the dispatcher 776 finds one or more such messages, it retrieves them from the blackboard 772. The messages can be persistent in the blackboard 772, remaining in the memory of the blackboard 772 after their retrieval by a component of the architecture 766. Because the blackboard 772 stores messages regardless of their source, and allows retrieval of those messages by any component of the architecture 766, the blackboard 772 is highly scalable to accommodate the use of an arbitrarily large number of digital assistants 700, dispatchers 776, sensor, actuators, and other components. The physical location of execution of the blackboard 772 is flexible. As one example, the blackboard 772 runs on a server cluster in the cloud. As another example, the blackboard 772 runs on a portable electronic device 200 of the user, such as an iPhone® iPhone® or iPad® device from Apple Inc. of Cupertino, Calif. As another example, the blackboard 772 runs on a server or home automation device locally at the user's dwelling and/or office. As another example, the blackboard 772 is itself distributed among a number of different devices associated with the user.
When a component of the architecture 766 posts a message to the blackboard 772, in some embodiments, that component does not have information regarding which other component or components will read it. In this way, two or more of the components of the architecture need not have direct knowledge of or communication with one another. The lack of a requirement for direct knowledge of and communication with each individual component further provides for scalability of the blackboard 772 for user in arbitrarily large architectures 766. The blackboard 772 allows for geographic distribution of components of the architecture 776, which communicate through network connections and can be distributed across locations. Further, because the components of the architecture 766 need not have direct knowledge of or connection to one another, individual components can be changed, upgraded or redeployed more easily. For example, if a component is associated with an action in a message and that component is replaced with a new, different component associated with that action, the component that generated the message need not have any knowledge of that replacement; it generates the same message regardless of which component picks it up. Still further, the blackboard 772 provides for a resilient architecture 766. If a component of the architecture 766 is broken, missing, or otherwise nonfunctional, a different component of the architecture 766, such as a backup, can generate messages and/or pick up messages instead of the nonfunctional components, allowing for smooth continued operation of the architecture 766.
Each message may be in any suitable format. According to some embodiments, the messages include SMS messages, which allows for connectivity across devices utilizing a widely-adopted, low-bandwidth standard. According to some embodiments, the messages include messages utilizing the iMessage® software feature of Apple Inc., of Cupertino, Calif. According to some examples, all of the messages are in the same format. According to other examples, at least one of the messages is in a different format than the others. Because interactions between the components of the architecture 776 take place through simple messages containing text, the blackboard 772 allows individual components to be implemented in different programming languages, and to run on different platforms, while being able to work together by individually posting messages to and retrieving messages from the blackboard 772.
According to some embodiments, the blackboard 772 operates in an orchestration mode. In the orchestration mode, the blackboard 772 orchestrates performance of tasks and delegates the tasks to particular components of the architecture. The blackboard 772 devices which component is better able to execute a particular task based on the capabilities of that component, the location of that component, and the context of that component and of that task. For example, a person may request the virtual assistant 700 to “wake up my son an hour before his dentist appointment.” In this particular example, the virtual assistant 700 disambiguates “son,” using the contacts module 237 and a user designation of a particular contact as “son,” and generates a message and transmits that message to the blackboard 772. That message includes a query about the time of the dentist appointment, and an action to wake the son an hour before then. In some embodiments of the orchestration mode, the blackboard 772 affirmatively determines which component of the architecture 766 to query about the time of the dentist appointment. In addition, in some embodiments of the orchestration mode, the blackboard 772 selects the component better suited to waking the son (e.g., the son's iPhone® device, iPad® device, Apple TV® digital media extender, home automation enabled by HomeKit*™ hardware and software technology, all of Apple Inc. of Cupertino, Calif.) and delegates the action of waking the son to that component.
According to some embodiments, the blackboard 772 operates in a subscription mode. In subscription mode, each component subscribes to the blackboard 772 for a particular task. For example, the dispatcher 776, which is associated with the door lock 782 subscribes to the blackboard 772 for the particular tasks of “unlock door lock 782” and “lock door lock 782.” According to some embodiments, the door lock 782 (as well as other sensors and/or actuators) communicates directly with the blackboard 772 without intermediation by a dispatcher 776. The blackboard 772 delegates performance of that particular task to the component that subscribed to that particular task. As used in this document, the term “delegation” includes transmitting to a component subscribed to a task a notification that a message associated with that task has been received at the blackboard 772 to inform the component a message awaits retrieval; “delegation” also includes forwarding or otherwise transmitting that message to that component with or without a separate notification to that component.
According to some embodiments, the blackboard 772 operates in a distribution mode. In the distribution mode, a component of the architecture 766 such as the first digital assistant 700a determines which other components of the architecture 766 will be involved in execution of a task or set of tasks, and transmits to the blackboard 772 a request for the blackboard 772 to communicate messages to and from those components for task execution. The blackboard 772 then delegates performance of individual tasks to those components. For example, a user requests the first digital assistant 700a to “ask the iPad in my office to play jazz.” In this example, the first digital assistant 700a identifies the iPad® device of Apple Inc. of Cupertino, Calif. in the office as the component of the architecture 766 that will play jazz, and transmits to the blackboard 772 a request for the blackboard 772 to communication messages to and from that particular iPad® device for task execution.
According to some embodiments, the blackboard 772 combines two or more of the orchestration mode, the subscription mode, and the distribution mode in the execution of one or more tasks. The flexibility provided by combining different modes allows the blackboard 772 to handle complex task execution.
The blackboard 772 is configured to transmit one or more messages to, and receive one or more messages from, the message gateway 770 and the dispatcher 776, according to some embodiments. In some embodiments, the message gateway 770 is configured to transmit and receive messages; the blackboard 772 is configured to store those messages in chronological order, and the dispatcher 776 is configured to interface with the physical world. For example, the dispatcher 776 is connected to a sound system 778, a proximity sensor 780, and a door lock 782. The dispatcher 776 is configured to control the sound system 778, to receive input from the proximity sensor 780, and to control the door lock 782. According to other examples, the dispatcher 776 is connected to more, fewer, or different items. Optionally, the first digital assistant 700a and/or second digital assistant 700b are configured to transmit one or more messages and/or commands to, and receive one or more messages and/or inputs from, the dispatcher 776 directly.
According to one example, the first digital assistant 700a transmits a message to the message gateway 770, which receives the message and forwards the message to the blackboard 772. The second digital assistant 700b retrieves that message from the blackboard 772. If the second digital assistant 700b takes action based on that message, the second digital assistant 700b transmits a message to the blackboard 772, which is forwarded to the dispatcher 776. The dispatcher 776 then, for example, actuates the door lock 782, allowing the door to be opened. While
According to some embodiments, the blackboard 772 can connect to at least one external service 784. Such a connection may be made only when necessary, and need not be a permanent connection. According to some embodiments, the blackboard 772 can connect to an external service 784 providing information, such as weather information, restaurant information, traffic information; to an external service 784 providing a physical service, such as transportation or food delivery; or to any other type of external service 784 useful in executing a plan.
The blackboard 772 retains the messages that move through it in chronological order, sorted by association of those messages with a particular user request, according to some embodiments. The messages include information relating to the originator, as well as content, according to some embodiments. In some embodiments, the messages are retained indefinitely until the user request for service associated with those messages has been fulfilled. In some embodiments, the messages are retained for a long duration, such as six months or one year. In this way, the blackboard 772 allows not just for intermediation between or among two or more digital assistants 770, but also for tracking of actions that take a long time to fulfill. For example, an action may be contingent upon an input that is not received for days, weeks or months after the user request for service is made. Despite that passage of time, the blackboard 772 retains the messages associated with a particular user request, to allow delayed and/or contingent fulfillment of a user request. Intermediation is performed by storing messages chronologically, sorted by association of those messages with a particular user request, regardless of the origin of those messages. According to some embodiments, the blackboard 772 need not be used. Instead, according to some embodiments, particularly for simple plans, the first digital assistant 700a generates a plan that includes instructions for executing part of the plan at a later time, or in concert with a different electronic device. According to some embodiments, during execution of such a plan, the first digital assistant 700a sends at least one message directly to another device, or receives a direct input from an internal sensor of the electronic device 200 or device associated with the electronic device 200, or transmits a direct output to an internal actuator of the electronic device 200 or device associated with the electronic device 200.
The plan can be distributed, executed and/or delegated by different devices. The orchestration of instructions within a particular plan can be centralized—for example by the blackboard 772 in the architecture 766—or can be distributed with each device executing one or more instructions, and delegating other instructions to other devices.
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.
Referring to
As illustrated in the example of
The at least one plan template 802 can be considered to be a different kind of domain within the ontology 760, referring also to
For example, referring to
One or more of the instructions 804 default to a particular input, output or contingent input 806 in the absence of user input, in some embodiments. For example, where the user sets the default door to “front door,” the user need not specify the particular door when requesting the service “let a visitor into my home.” Optionally, one or more default values of input, output or contingent input 806 for at least one plan template 802 are configured at system setup by the user or by an entity other than the user. For example, a plan template for “receive calls from a family member” includes an output to “always answer a call from a family member” as a default value. The user can override or change the default, according to some embodiments. For example, if the user has limited mobility for medical reasons, the user can change the plan template for “receive calls from a family member” default output of “always answer a call from a family member” to “play family member a message that I am healthy but recovering from knee surgery.”
As illustrated in the example of
Referring to
Referring to
As another example, in order to determine when the visitor is arriving, the digital assistant initiates communication with the visitor directly. The digital assistant sends an iMessage® message 818 (referring to the iMessage® software feature of Apple Inc. of Cupertino, Calif.) to Tomas, such as through the instant messaging module 241, asking “Tomas, when will you arrive at Pierre's apartment?” As other examples, the digital assistant contacts Tomas through other modalities, such as SMS messaging, voice communication, and/or electronic mail. The digital assistant itself initiates this contact with Tomas, using information associated with Tomas stored in or accessible through the contacts module 237. In response, Tomas transmits a message 820 back to the digital assistant, responding “in a couple of hours.” The digital assistant disambiguates this response based on the current time, which is kept locally on the electronic device 200 and/or transmitted as a signal by a wireless carrier or other service provider and received at the electronic device 200. The digital assistant adds two hours to the current time and then determines the date associated with that time (for example, if the current time is 11:20 p.m., then the addition of two hours to that time results in an expected arrival date one day later than the current date). In response, the digital assistant optionally sends a reply message 822 to Tomas, acknowledging Tomas' response: “OK, thanks!”
Referring to
Upon arriving at the apartment, referring also to
Recognizing that a person is at the door, the digital assistant 700b with authority to control the door lock 782 requests, over a speaker, on a screen by the door, on the electronic device 200 of Tomas, or in any other suitable manner, that Tomas provide his name, according to some embodiments. In this example, Tomas speaks his name. The digital assistant 700b then requests the password. Tomas communicates the password to the digital assistant 700b, such as through a microphone that forms part of the sound system 778. Upon determining that the password provided by Tomas matches the expected password, the digital assistant 700b transmits a message to the blackboard 772, which is forwarded to or retrieved by the dispatcher 776, for the dispatcher 776 to unlock the door lock 782. After unlocking the door for Tomas, the digital assistant 700b alerts the user Pierre, according to some embodiments. In this example, the digital assistant 700b transmits a message to the blackboard 772, which is forwarded to or retrieved by the message gateway 770 and then transmitted onward to Pierre's digital assistant. Referring to
In this example, the blackboard 772 provided for intermediation between three different digital assistants: Pierre's digital assistant 700a, Tomas' digital assistant 700, and the digital assistant 700b at Pierre's apartment. As discussed above, the blackboard 772 retains the messages that move through it in chronological order, sorted by association of those messages with a particular user request, according to some embodiments. By receiving, storing, and transmitting (or allowing retrieval of) those messages by all three digital assistants 700 involved in the user request to “let Tomas in my apartment when he arrives,” the user intent expressed in that user request is effectuated. The blackboard 772 stores the messages received from and sent to each digital assistant 700, providing a location that any of the three separate digital assistants can search in order to find information relating to the user request. The plan generated by the user's digital assistant 700, based on the plan template 802 corresponding to the user request, includes instructions and/or information relating to the other digital assistants 700 that are involved in effectuating the user request, according to some embodiments.
Further, in this example, Pierre's digital assistant 700a has communicated with the digital assistant 700b associated with Pierre's apartment prior to Tomas' arrival; otherwise, the digital assistant 700b associated with Pierre's apartment would not be able to assist in the execution of the plan. In the interest of clarity, communication between the digital assistants 700a, 700b prior to the arrival of Tomas is not described in detail. However, according to some embodiments, executing the plan includes identifying other entities, such as other digital assistants 700b, to which output is provided and from which input is received, and to which performing at least one of the instructions and sub-tasks included in the plan are delegated, in order to effectuate the plan. In this example, performance of at least some of the instructions of the plan was delegated from Pierre's digital assistant 700a to the digital assistant 700b associated with Pierre's apartment.
Returning to
Referring to
Pierre may wish to make his guest more comfortable while he waits. Referring to
In order to obtain sufficient information to generate a plan based on that plan template, Pierre's digital assistant 700a obtains information about Tomas' favorite music. As one example, Pierre's digital assistant 700a initiates communication with Tomas' digital assistant. This communication occurs through the blackboard 772 of
Referring to
Returning to exception handling, and with reference to the first example, Pierre's digital assistant 700a generated a plan to let Tomas into his apartment. During execution of that plan, the digital assistant 700b associated with Pierre's apartment awaits contingent input associated with Tomas' arrival. Referring to
Returning to the first example, Pierre's digital assistant 700a generated a plan to let Tomas into his apartment. During execution of that plan, the digital assistant 700b associated with Pierre's apartment awaits contingent input associated with Tomas' arrival. Referring to
As used in the description of the flow diagram 900, and in this document as a whole, the terms “virtual assistant” and “digital assistant” are used interchangeably and have the same meaning. For the avoidance of doubt, the term “virtual assistant” means the digital assistant 700.
As described below, method 900 provides an intuitive way for interacting with a digital assistant. The method reduces the cognitive burden on a user when using a digital assistant, thereby creating a more efficient human-machine interface. For battery-operated computing devices, enabling a user to utilize a digital assistant more accurately and more efficiently conserves power and increases the time between battery charges.
At the beginning of process 900, the digital assistant receives 902 an unstructured natural language user request for a service from a digital assistant. That unstructured natural language user request includes one or more words. Where the electronic device (104, 200, 400, 600) includes or is associated with a microphone 213, that user input may be received through the microphone 213. The user input may also be referred to as an audio input or audio stream. In some embodiments, the stream of audio can be received as raw sound waves, as an audio file, or in the form of a representative audio signal (analog or digital). In other embodiments, the audio stream can be received at a remote system, such as a server component of a digital assistant. The audio stream can include user speech, such as a spoken user request. In an alternate embodiment, the user input is received in textual form instead of as speech. In some embodiments, the audio stream is converted from speech to text by ASR processing prior to, or during, analysis by the digital assistant. Such conversion may be performed as described above.
Optionally, the digital assistant determines 904 whether the user request of block 902 is a plan trigger. A “plan trigger” is a request that is associated with one or more plan templates 802, as opposed to a simple task request that is not associated with one or more plan templates 802. For example, a user request in block 902 to “set an alarm for 8 a.m.” is not a plan trigger; it is a task request that can be fulfilled by the digital assistant without reference to a plan template. As another example, a user request to “let my mother in my apartment when she arrives” corresponds to a plan template 802, and thus is a plan trigger. Generally speaking, more complex actions, and actions that rely upon contingent inputs, are associated with plan triggers. According to some embodiments, when the determination 904 is made, the user request is compared to the tasks that can be fulfilled by the digital assistant without reference to a plan template 802; if the user request does not match any such tasks, then the user request is analyzed as a potential plan trigger. According to other embodiments, when the determination 904 is made, the user request is compared to a list of plan triggers; if the user request does not match any such tasks, then the user request is determined to not include a plan trigger.
If the user request of block 902 is not a plan trigger, then the digital assistant processes 906 the user request other than by generation of a plan based on at least one plan template 802. In the example above, a user request to ‘set an alarm for 8:00 a.m.” is handled in a standard manner by the digital assistant, without the need to search for a plan template 802 or generate a plan.
If the user request of block 902 is a plan trigger, then the digital assistant determines 908 whether the user request corresponds to at least one of a plurality of plan templates 802. As set forth above, the plan templates 802 are associated with a variety of different actions. For example, plan templates 802 may include “let [guest] into my apartment when [guest] arrives,” “call a [cab/shared ride] for [guest] when [guest] leaves my house,” and “buy tickets for [movie] when they go on sale.” The plan templates 802 need not remain static; existing plan templates 802 are modified over time to improve their functionality, and new plan templates 802 are added over time, according to some embodiments.
If the user request of block 902 does not correspond to at least one of a plurality of plan templates 802, then the digital assistant foregoes 912 selection of a plan template 802. The user request of block 902 may be out of scope of any of the plan templates 802, may be outside the capabilities of a digital assistant, or may not be capable of being understood. For example, if the user request of block 902 is “make me a chocolate soufflé,” and no plan template 802 exists for making a chocolate soufflé, the digital assistant necessarily foregoes selection of a plan template 802. Optionally, the digital assistant informs the user that the user request of block 902 cannot be satisfied.
If the user request of block 902 corresponds to at least one of a plurality of plan templates, then the digital assistant selects 910 one of the plurality of plan templates 802 that best corresponds to the user request. This selection may be performed in a manner the same as, or similar to, the manner in which a domain responsive to a user request is selected, as described herein, according to some embodiments. According to other embodiments, the digital assistant selects 910 one of the plurality of plan templates 802 that best corresponds to the user request in any other suitable manner or with any other suitable methodology.
Next, the digital assistant begins 914 processing the user request according to the selected plan template 802. In order to generate a plan based on the plan template, the digital assistant determines 916 whether sufficient information is available to the digital assistant for the digital assistant to generate a plan based on the selected plan template. As described above, “sufficient information” is the minimum information with which the digital assistant can generate a plan. As described above, one or more of the inputs 806 of the plan template 802 are placeholders awaiting information. Where at least one of those inputs 806 is not optional in order for a plan to be generated, sufficient information exists where information is available to the digital assistant for the virtual assistant to populate each non-optional input field.
If sufficient information is available to the virtual assistant to generate a plan based on the selected plan template 802, the digital assistant generates 918 a plan based on the selected plan template 802. In some embodiments, once the digital assistant 700 identifies selects a plan template 802 based on the user request, the digital assistant 700 generates a plan based on the selected plan template. As used in this document, the term “plan” refers to a set of two or more instructions that is executable on at least one electronic device. A plan differs from a task request, in which a single instruction is performed based on a user request. The term “instruction,” as used in the context of a plan or task request, refers to a granular step, and not a program instruction (e.g., a program language command). The plan includes at least one interaction with a user, an entity other than the user, an external service. or other entity, according to some embodiments. The plan utilizes at least one sensor (e.g., proximity sensor 780), and/or at least one actuator (e.g., door lock 782), according to some embodiments. The plan utilizes multiple devices, according to some embodiments. The plan executes at least one instruction at a future time, such as a predetermined future time (e.g., tomorrow at 8:00 a.m.) or upon being triggered by an external event (e.g., receipt of input), according to some embodiments. According to some embodiments, examples of an event include an interaction or communication with another user or users, receipt of biometric data (e.g., heart rate data from the user's Apple Watch® wrist wearable device (a product of Apple Inc. of Cupertino, Calif.), and receipt of environmental data (e.g., a weather report from an external service, local temperature as determined by a sensor)
When the digital assistant generates 918 a plan, it does so based on the content of the user request as well as the plan template 802. The user request may include at least one of the inputs to the plan template 802 that constitute sufficient information to generate a plan. The digital assistant 700 converts the passive structure of the plan template 802 into an actionable plan that can be executed by the digital assistant 700. In some embodiments, the digital assistant generates 918 a plan in part by selecting modules of the electronic device 200 and digital assistant 700 for performing at least some of the instructions and sub-tasks included in the plan. In some embodiments, the digital assistant generates 918 a plan in part by identifying other entities, such as other users, other digital assistants, and external services, to which output is provided and from which input is received, and to which performing at least one of the instructions and sub-tasks included in the plan is delegated, in order to effectuate the plan. After the plan is generated, the process 900 moves optionally to block 940 described in greater detail below.
If sufficient information is not available to the virtual assistant to generate a plan based on the selected plan template 802, in this example the digital assistant obtains 920 sufficient information to generate a plan based on the selected plan template 802. The digital assistant may retrieve sufficient information in a variety of manners. For example, the digital assistant can obtain sufficient information from the user, from entities other than the user, from external services, or from the electronic device itself.
Optionally, the digital assistant initiates 922 communication with the user to request sufficient information to generate a plan based on the selected plan template. For example, in
Optionally, in response to the initiation of communication with the user, the digital assistant receives 924 sufficient information from the user to generate a plan based on the selected plan template. For example, in
Optionally, the digital assistant initiates 926 communication with an entity other than the user to request sufficient information to generate a plan based on the selected plan template. For example, in
Optionally, in response to the initiation of communication with an entity other than the user, the digital assistant receives 928 sufficient information from the entity other than user to generate a plan based on the selected plan template. For example, in
Optionally, the digital assistant initiates 932 communication with an external service 784 to request sufficient information to generate a plan based on the selected plan template 802. For example, in
Optionally, in response to the initiation of communication with an external service, the digital assistant receives 934 sufficient information from the entity other than user to generate a plan based on the selected plan template. For example, with reference to the examples above, the digital assistant receives information from the Apple Music™ streaming radio service that Tomas likes samba, and that Great Wall of China is a Chinese restaurant within 2 miles of the user's house that takes reservations and that receives 4 out of 5 stars for food quality, respectively. Having sufficient information to generate a plan, the process continues to block 937, in which the digital assistant generates a plan based on the selected plan template 802, using the obtained information.
Optionally, the digital assistant obtains 936 sufficient information from the electronic device itself to generate a plan based on the selected plan template 802. For example, in the example described above with regard to
The digital assistant may perform more than one of the optional blocks 952, 956, 932, and 936, in series or in parallel in order to obtain sufficient information, according to some embodiments. By initiating communication with multiple different sources of information, and searching the electronic device for information, the digital assistant has a greater likelihood of finding information. In addition, if such information is available from different sources, the digital assistant can utilize the information that is received first, thereby speeding up the process of responding to the user request.
Optionally, the digital assistant generates 938 the plan based in part on at least one of device context and user context. User context includes information associated with the user of the electronic device 200. In accordance with some embodiments, user context includes the content of the user input. In accordance with some embodiments, user context includes demographic information about the user, such as the user's age, gender, or the like. In accordance with some embodiments, the user context includes media associated with the user, regardless of the storage location of the media. In accordance with some embodiments, the user context includes content associated with the user. In accordance with some embodiments, the user context includes but is not limited to the content of messages, such as SMS messages, messages utilizing the iMessage® software feature of Apple Inc., of Cupertino, Calif., instant messaging messages, and electronic mail. In accordance with some embodiments, the user context includes contact information, such as information stored in or by the contacts module 237. In accordance with some embodiments, the user context includes at least one location associated with the user. For example, the user designates one or more specific locations with unique identifiers, such as “home,” “Mom's house,” or “work.” The user may do so by entering an address, by providing a touch input on a map displayed on the display 212, or in any other suitable manner. The user has identified a limited number of locations specifically, and the digital assistant stores those identifiers. Such identifiers are not addresses themselves, but are associated with addresses and/or navigation coordinates (such as GPS coordinates). Such locations are assumed to be significant to the user, and can be useful in responding when responding to user requests such as “make a business lunch reservation at noon tomorrow near work.” According to some embodiments, user context includes biometric information about the user, such as heart rate or sleep state.
Device context includes information associated with the electronic device 200 itself. According to some embodiments, device context includes a location of the electronic device 200. According to some embodiments, device context includes motion of the electronic device 200, such as whether the electronic device 200 is stationary or moving, how fast the electronic device 200 is moving, in what direction the electronic device 200 is moving, and whether the electronic device 200 is accelerating. Such motion can be determined by utilizing the accelerometer(s) 268 and/or the GPS module 235. According to some embodiments, the device context includes proximity of the electronic device 200 to a second electronic device, such as a home automation system, a wrist wearable device such as the Apple Watch® wrist wearable device of Apple Inc. of Cupertino, Calif., a television interface such as the Apple TV® digital media extender of Apple Inc. of Cupertino, Calif., a vehicle, a different electronic device belonging to another user, or other electronic device. According to some embodiments, device context includes weather conditions in proximity to the electronic device 200, such as obtained from an external service 784 based on the location of the electronic device.
The digital assistant generates 938 the plan based in part on at least one of device context and user context by utilizing at least one context to obtain sufficient information to generate a plan, according to some embodiments. According to some embodiments, the digital assistant utilizes at least one of device context and user context to provide details of an actionable plan that can be executed by the digital assistant 700 and the electronic device 200.
Optionally, the digital assistant then executes 940 the generated plan. The digital assistant uses the plan to take action to fulfill the user request. Examples of executing the generated plan are described in
Optionally, during execution of the plan, the digital assistant detects 942 an exception to the plan. As set forth above, the term “exception” refers to an unexpected input or event that is not consistent with the plan to fulfill a user request 800 based on the plan template 802.
Upon encountering an exception, optionally the digital assistant determines 946 whether the exception can be handled according to the plan. If the exception can be handled according to the plan, the digital assistant handles 948 the exception according to the plan. In the example above illustrated in
If the exception cannot be handled according to plan, the digital assistant obtains 950 sufficient information for the digital assistant to handle the exception. The digital assistant does so in any suitable manner. Optionally, the digital assistant can obtain sufficient information from the user, from entities other than the user, from external services, or from the electronic device itself.
Optionally, the digital assistant initiates 952 communication with the user to request sufficient information for the digital assistant to handle the exception. For example, in
Optionally, in response to the initiation of communication with the user, the digital assistant receives 954 sufficient information from the user for the digital assistant to handle the exception. For example, in
Optionally, the digital assistant initiates 956 communication with an entity other than the user from whom the request for service was received in order to request sufficient information for the virtual assistant to handle the exception. As one example, the digital assistant initiates 956 communication to Tomas, asking whether Tomas would prefer to enter, or return later. The digital assistant may message Tomas with SMS messaging or messages utilizing the iMessage® software feature of Apple Inc., of Cupertino, Calif., or may contact the other user in any other suitable method, such as by placing a telephone call to the other user, sending the other user electronic mail, or any other suitable form of communication. The entity other than the user is not limited to another user; as described above, the entity other than the user includes a second digital assistant under the control of the user but that is not associated with the electronic device 200, such as a digital assistant associated with the user's dwelling, according to some embodiments. According to some embodiments, the entity other than the user is a digital assistant that is not under the control of the user, such as a digital assistant associated with an electronic device 200a belonging to a friend or family member.
Optionally, in response to the initiation of communication with an entity other than the user, the digital assistant receives 958 sufficient information from the entity other than user for the digital assistant to handle the exception. For example, Tomas responds that he will go get a cup of coffee and come back later. Such a response may be received by SMS messaging, messages utilizing the iMessage® software feature of Apple Inc., of Cupertino, Calif., speech of the other user (converted to text as described above), electronic mail, or any other suitable message format. Having sufficient information, the process continues to handle 972 the exception with the received information. The digital assistant 700 transmits a message to the second digital assistant to leave the door locked and to continue to wait for the contingent input of Tomas' arrival, closer to the time Tomas had been expected to arrive.
Optionally, the digital assistant initiates 964 communication with an external service 784 to request sufficient information for the virtual assistant to handle the exception. For example, in
Optionally, in response to the initiation of communication with an external service, the digital assistant receives 966 sufficient information from the external service 784 for the digital assistant to handle the exception. For example, with reference to the example above, the digital assistant receives information from the Apple Music™ streaming radio service that Tomas likes samba. Having sufficient information, the process continues to handle 972 the exception with the received information. The digital assistant 700 transmits a message to the second digital assistant to play samba music for Tomas.
Optionally, the digital assistant monitors 974 execution of the plan over time for receipt of at least one input upon which execution of the plan is contingent. As defined above, contingent inputs are inputs without which the plan cannot complete execution. For example, in the example above in which the user request is to let Tomas into his apartment when he arrives, one contingent input is the presence of Tomas, and another contingent input is his utterance or entry of the password. Until one or both of those contingent inputs is received, the execution of the plan is suspended. Execution of the plan can be suspended indefinitely, according to some embodiments.
Optionally, the digital assistant receives 976 at least one contingent input. As described above, a message thread on the blackboard 772 may be retained indefinitely, allowing the digital assistant to store the progress of the plan, and providing a basis for periodic active monitoring of the plan by the digital assistant, according to some embodiments. In such embodiments, the digital assistant periodically searches for the presence of the contingent input. According to some embodiments, the digital assistant passively monitors the plan, and upon receipt of a contingent input, locates a suspended plan and matches that contingent input to the plan. The digital assistant continues 978 execution of the plan upon receipt of all conditional inputs required for the plan to proceed. Different contingent inputs may be spaced apart in time, and the receipt of the first contingent input allows the digital assistant to continue to execute the plan to the point where another contingent input is required. For example, a plan may have a first contingent input that is expected within 10 minutes, and a second contingent input required the next day. The digital assistant will execute the plan until the first contingent input is required, continue to execute the plan after the first contingent input is received, and then suspend execution until the second contingent input is required.
Optionally, execution of the plan causes 980 at least one physical output. For example, as described above, after Tomas has arrived at Pierre's apartment and provides the password, upon determining that the password provided by Tomas matches the expected password, the digital assistant 700b transmits a message to the blackboard 772, which is forwarded to or retrieved by the dispatcher 776, for the dispatcher 776 to unlock the door lock 782. The user's digital assistant 700a causes the door lock 782 to be unlocked—a physical output—by transmitting to the digital assistant 700b the conditions to be met for Tomas to be admitted. Thus, the process 900 allows and facilitates interactions between the user's digital assistant and the physical world. The virtual assistant optionally generates 982 multimodal output; that is, two or more of text, audio, messages, electronic mail, and physical output. The process 900 and the architecture 766 used to perform the method provide a rich set of outputs that are not limited in the number than can be performed at once, or across time.
Optionally, as described above in several examples, in the course of executing the plan the digital assistant initiates 984 transmission of at least one message. Such messages are SMS messages, messages utilizing the iMessage® software feature of Apple Inc., of Cupertino, Calif., electronic mail, telephone calls, instant messages, or any other suitable message format, according to some embodiments. The ability of the digital assistant to initiate transmission of a message to an entity other than the user allows the digital assistant to make complex plans and handle contingent inputs and exceptions, according to some embodiments. Such initiation may happen a substantial period of time after the user request, and differs from a communication initiated to the user immediately after the user request that is for disambiguation of that user request. Similarly, according to some embodiments, optionally the digital assistant presents 986 output to an entity other than the user. For example, as described above with regard to
Optionally, the digital assistant notifies 988 the user after execution of the plan is complete. For example, as described above with regard to
In accordance with some embodiments,
As shown in
In some embodiments, the processing unit 1108 is configured to receive (e.g., with receiving unit 1110) an unstructured natural-language user request for a service from a virtual assistant; determine (e.g., with determining unit 1112) whether the user request corresponds to at least one of a plurality of plan templates accessible to the virtual assistant, based on the content of the user request and the content of the plan templates; in accordance with a determination that the user request corresponds to at least one of the plurality of plan templates, select (e.g., with selecting unit 1114) one of the plurality of plan templates; and in accordance with a determination that the user request fails to correspond to at least one of the plurality of plan templates, forego selection (e.g., with selecting unit 1114) of a plan template; and in response to selection of one of the plan templates, begin to respond (e.g., with responding unit 1116) to the user request according to the selected plan template.
In some embodiments, the processing unit 1108 further includes a generating unit 1118 and an obtaining unit 1120, where the processing unit 1108 is further configured to determine (e.g., with determining unit 1112) whether sufficient information is available to the virtual assistant for the virtual assistant to generate a plan based on the selected plan template 802; in accordance with a determination that sufficient information is available to the virtual assistant for the virtual assistant to generate a plan based on the selected plan template, generate (e.g., with generating unit 1118) a plan based on the selected plan template with the virtual assistant; and in accordance with a determination that insufficient information is available to the virtual assistant for the virtual assistant to generate a plan based on the selected plan template: obtain (e.g., with obtaining unit 1120) sufficient information to generate a plan based on the selected plan template; and in response to sufficient information being obtained, generate (e.g., with generating unit 1118) a plan based on the selected plan template with the virtual assistant.
In some embodiments, the processing unit 1108 is further configured to in accordance with a determination that sufficient information is available to the virtual assistant for the virtual assistant to generate a plan based on the selected plan template, initiate (e.g., with initiating unit 1122) communication with the user to request sufficient information to generate a plan based on plan template; and in response to the initiation, receive (e.g., with receiving unit 1110) sufficient information to generate a plan based on the plan template.
In some embodiments, the processing unit 1108 is further configured to in accordance with a determination that sufficient information is available to the virtual assistant for the virtual assistant to generate a plan based on the selected plan template, initiate (e.g., with initiating unit 1122) communication with an entity other than the user to request sufficient information to generate a plan based on the plan template; and in response to the initiation, receive (e.g., with receiving unit 1110) sufficient information to generate a plan based on the plan template.
In some embodiments, the processing unit 1108 is further configured to in accordance with a determination that sufficient information is available to the virtual assistant for the virtual assistant to generate a plan based on the selected plan template, initiate (e.g., with initiating unit 1122) communication with an external service to request sufficient information to generate a plan based on the plan template; and in response to the initiation, receive (e.g., with receiving unit 1110) sufficient information to generate a plan based on the plan template.
In some embodiments, the processing unit 1108 is further configured to in accordance with a determination that sufficient information is available to the virtual assistant for the virtual assistant to generate a plan based on the selected plan template, obtain (e.g., with obtaining unit 1120) sufficient information from the electronic device to generate a plan based on the plan template.
In some embodiments, the sufficient information from the electronic device to generate (e.g., with generating unit 1118) a plan based on the plan template includes a time associated with task execution.
In some embodiments, the sufficient information from the electronic device to generate (e.g., with generating unit 1118) a plan based on the plan template includes a location of task execution.
In some embodiments, the sufficient information from the electronic device to generate (e.g., with generating unit 1118) a plan based on the plan template includes an identity of at least one person associated with task execution.
In some embodiments, the processing unit 1108 is further configured to: after receipt of the user request, determine (e.g., with determining unit 1112) whether the user request comprises a plan trigger; in accordance with a determination that the user request comprises a plan trigger, initiate (e.g., with initiating unit 1122) the determination whether sufficient information is available to the virtual assistant for the virtual assistant to generate a plan based on the selected plan template; and in accordance with a determination that the user request does not comprise a plan trigger, respond (e.g., with responding unit 1116) to the user request other than by generation of a plan based on at least one plan template.
In some embodiments, the processing unit 1108 is further configured to generate (e.g., with generating unit 1118) the plan based on the plan template and based in part on at least one of device context and user context.
In some embodiments, the device context includes a location of the device.
In some embodiments, the device context includes motion of the device.
In some embodiments, the device context includes proximity to a second electronic device.
In some embodiments, the device context includes weather conditions in proximity to the electronic device.
In some embodiments, the user context includes the content of the user input.
In some embodiments, the user context includes media associated with the user.
In some embodiments, the user context includes demographic information associated with the user.
In some embodiments, the user context includes data associated with user content accessible by the device.
In some embodiments, the user context includes content of messages stored on the electronic device.
In some embodiments, the user context includes contact information.
In some embodiments, the user context includes at least one location associated with the user.
In some embodiments, the user context includes biometric information.
In some embodiments, the processing unit 1108 further includes an executing unit 1124, where the processing unit 1108 is further configured to execute (e.g., with generating unit 1118) the generated plan.
In some embodiments, the processing unit 1108 further includes a detecting unit 1126 and a handling unit 1128; where the processing unit 1108 is further configured to: during execution of the plan, detect (e.g., with detecting unit 1126) an exception to the plan; and determine (e.g., with determining unit 1112) whether the exception can be handled according to the plan; in accordance with a determination that the exception can be handled according to the plan, handle (e.g., with handling unit 1128) with the virtual assistant, the exception with information associated with the plan; and in accordance with a determination that the exception cannot be handled according to the plan: obtain (e.g., with obtaining unit 1120) sufficient information for the virtual assistant to handle the exception; and handle (e.g., with handling unit 1128) with the virtual assistant, the exception with the obtained information.
In some embodiments, the processing unit 1108 is further configured to in accordance with a determination that the exception cannot be handled according to the plan, initiate (e.g., with initiating unit 1122) communication with the user from whom the request for service was received to request sufficient information for the virtual assistant to handle the exception; and in response to the initiation, receive (e.g., with receiving unit 1110) sufficient information for the virtual assistant to handle the exception.
In some embodiments, the processing unit 1108 is further configured to in accordance with a determination that the exception cannot be handled according to the plan, initiate (e.g., with initiating unit 1122) communication with an entity other than the user to request sufficient information for the virtual assistant to handle the exception; and in response to the initiation, receive (e.g., with receiving unit 1110) sufficient information for the virtual assistant to handle the exception.
In some embodiments, the processing unit 1108 is further configured to in accordance with a determination that the exception cannot be handled according to the plan, initiate (e.g., with initiating unit 1122) communication with an external service to request sufficient information for the virtual assistant to handle the exception; and in response to the initiation, receive (e.g., with receiving unit 1110) sufficient information for the virtual assistant to handle the exception.
In some embodiments, the processing unit 1108 further includes a monitoring unit 1132; wherein the processing unit 1108 is further configured to: monitor (e.g., with monitoring unit 1132) execution of the plan over time with the virtual assistant for receipt of at least one input upon which execution of the plan is contingent; receive (e.g., with receiving unit 1110) the at least one input; and continue (e.g., with generating unit 1118) execution of the plan. In some embodiments, at least one input includes multimodal input.
In some embodiments, the processing unit 1108 further includes a causing unit 1134; wherein the processing unit 1108 is configured to execute (e.g., with generating unit 1118) the plan; the processing unit 1108 accordingly further configured to cause (e.g., with causing unit 1130) at least one physical output.
In some embodiments, the processing unit 1108 is configured to execute (e.g., with generating unit 1118) the plan; the processing unit 1108 accordingly further configured to generate (e.g., with generating unit 1118) multimodal output.
In some embodiments, the processing unit 1108 is configured to execute (e.g., with generating unit 1118) the plan; the processing unit 1108 accordingly further configured to initiate (e.g., with initiating unit 1122) transmission of at least one message.
In some embodiments, the processing unit 1108 is further configured to cause (e.g., with causing unit 1130) presentation of output to an entity other than the user.
In some embodiments, the processing unit 1108 further includes a notifying unit 1136; wherein the processing unit 1108 is further configured to notify (e.g., with notifying unit 1136) the user after execution of the plan is complete.
The operations described above with reference to
As described below, method 1000 provides an intuitive way for handling messages to and from one or more virtual assistants. The method reduces the cognitive burden on a user when using a digital assistant, thereby creating a more efficient human-machine interface. For battery-operated computing devices, enabling a user to utilize a digital assistant more accurately and more efficiently conserves power and increases the time between battery charges.
At the beginning of process 1000, an electronic device receives 1002 from a virtual assistant a message associated with an action. Referring to
Next, according to some embodiments, the electronic device communicates 1006 the message to a second electronic device associated with the action. Such communication is performed in any suitable manner, such as described above with regard to the process 900. For example, such communication is “push” communication (e.g., initiated by the electronic device) or “pull” communication (e.g., initiated from outside the electronic device) according to some embodiments. Whether such communication is push communication, pull communication, a combination thereof, or a different kind of communication depends on whether the blackboard 772 is operating in orchestration mode, subscription mode, distribution mode, or a combination thereof, according to some embodiments.
According to some embodiments, the electronic device transmits 1008 the message to a second electronic device associated with the action. For example, this transmission can be a push communication that is associated with the orchestration mode. Such transmission is performed as described above, according to some embodiments. According to some embodiments, the electronic device 1008 receives 1010 a request for the message from a second electronic device associated with the action. For example, that second electronic device is the dispatcher 776, or a second electronic device associated with the second digital assistant 700b. In accordance with receipt of the request, the electronic device transmits the message to the second electronic device associated with the action. For example, this transmission can be a pull communication that is associated with the subscription mode. Such transmission is performed as described above, according to some embodiments.
According to some embodiments, communicating the message to a second electronic device associated with the action includes communicating 1014 the message to a second virtual assistant associated with the second electronic device. According to some embodiments, where the second electronic device is a dispatcher 776 or executes the dispatcher, the electronic device communicates 1016 the message to the dispatcher 776. Like the blackboard 772, physical location of execution of the dispatcher 776 is flexible. As one example, the dispatcher 776 runs on a server cluster in the cloud. As another example, the dispatcher 776 runs on a portable electronic device 200 of the user, such as an iPhone® iPhone® or iPad® device from Apple Inc. of Cupertino, Calif. As another example, the dispatcher 776 runs on a server or home automation device locally at the user's dwelling and/or office. As another example, the dispatcher 776 is itself distributed among a number of different devices associated with the user. According to some embodiments, in response to communication of the message to the dispatcher 776, the electronic device receives 1018 information from the dispatcher 776 related to at least one sensor associated with the dispatcher 776. As one example, a sensor is the proximity sensor 780, although at least one sensor can be configured to sense one or more other physical properties. The information received from the dispatcher 776 related to at least one sensor is used to provide contingent input to a plan template 802 during plan execution, such as described above. According to some embodiments, in response to communication of the message to the dispatcher 776, the electronic device receives 1020 information from the dispatcher 776 related to at least one actuator associated with the dispatcher 776. For example, the actuator is a sound system 778 and/or door lock 782, although at least one actuator can be configured to cause at least one physical effect. The information received from the dispatcher 776 related to at least one actuator confirms the actuation of such one or more actuators, and is used to provide notification to the user that the actuation has occurred, according to some embodiments.
Optionally, the electronic device receives 1020 a message from at least one additional virtual assistant, each message associated with an action. As described above, the blackboard 772 facilitates communication between multiple virtual assistants in a simple and scalable manner. The electronic device stores 1024 each such message, such as described above.
Optionally, the electronic device receives 1026 a message from at least one additional electronic device, each message associated with an action. Such electronic devices need not execute a complete or even partial virtual assistant, but include at least the capability to transmit messages to the blackboard 772 useful for task execution. The electronic device stores 1024 each such message, such as described above.
In accordance with some embodiments,
As shown in
As shown in
In some embodiments, the processing unit 1208 is configured to receive (e.g., with receiving unit 1210) from a virtual assistant a message associated with an action; store (e.g., with storing unit 1212) the message, and communicate (e.g., with communicating unit 1214) the message to a second electronic device associated with the action.
In some embodiments, the processing unit further includes a transmitting unit, where the processing unit is configured to communicate (e.g., with communicating unit 1214), the message to a second electronic device associated with the action; the processing unit accordingly further configured to transmit (e.g., with transmitting unit 1216) the message to a second electronic device associated with the action.
In some embodiments, the processing unit is configured to communicate (e.g., with communicating unit 1214), the message to a second electronic device associated with the action; the processing unit accordingly further configured to receive (e.g., with receiving unit 1210) a request for the message from a second electronic device associated with the action; and in accordance with receipt of the request, transmit (e.g., with transmitting unit 1216) the message to the second electronic device associated with the action.
In some embodiments, the processing unit is configured to communicate (e.g., with communicating unit 1214) the message to a second electronic device associated with the action; the processing unit accordingly further configured to communicate (e.g., with communicating unit 1214) the message to a second virtual assistant associated with the second electronic device.
In some embodiments, the second electronic device is a dispatcher; and the processing unit is configured to communicate (e.g., with communicating unit 1214) the message to a second electronic device associated with the action; the processing unit accordingly further configured to communicate (e.g., with communicating unit 1214) the message to the dispatcher.
In some embodiments, the processing unit is further configured to, in response to communication of the message to the dispatcher, receive (e.g., with receiving unit 1210) information from the dispatcher related to at least one sensor associated with the dispatcher.
In some embodiments, the processing unit is further configured to, in response to communication of the message to the dispatcher, receive (e.g., with receiving unit 1210) confirmation from the dispatcher related to performance by at least one actuator associated with the dispatcher of at least one action associated with the message.
In some embodiments, the processing unit is further configured to receive (e.g., with receiving unit 1210) a message from at least one additional virtual assistant, each message associated with an action; and store (e.g., with storing unit 1212) each message.
In some embodiments, the processing unit is further configured to receive (e.g., with receiving unit 1210) a message from at least one additional electronic device, each message associated with an action; and store (e.g., with storing unit 1212) each message.
The electronic device of claim 76, wherein at least one message is in SMS format.
The operations described above with reference to
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.
As described above, one aspect of the present technology is the gathering and use of data available from various sources to improve the delivery to users of content that may be of interest to them. The present disclosure contemplates that in some instances, this gathered data may include personal information data that uniquely identifies or can be used to contact or locate a specific person. Such personal information data can include demographic data, location-based data, telephone numbers, email addresses, home addresses, or any other identifying information.
The present disclosure recognizes that the use of such personal information data, in the present technology, can be used to the benefit of users. For example, the personal information data can be used to deliver targeted content that is of greater interest to the user. Accordingly, use of such personal information data enables calculated control of the delivered content. Further, other uses for personal information data that benefit the user are also contemplated by the present disclosure.
The present disclosure further contemplates that the entities responsible for the collection, analysis, disclosure, transfer, storage, or other use of such personal information data will comply with well-established privacy policies and/or privacy practices. In particular, such entities should implement and consistently use privacy policies and practices that are generally recognized as meeting or exceeding industry or governmental requirements for maintaining personal information data private and secure. For example, personal information from users should be collected for legitimate and reasonable uses of the entity and not shared or sold outside of those legitimate uses. Further, such collection should occur only after receiving the informed consent of the users. Additionally, such entities would take any needed steps for safeguarding and securing access to such personal information data and ensuring that others with access to the personal information data adhere to their privacy policies and procedures. Further, such entities can subject themselves to evaluation by third parties to certify their adherence to widely accepted privacy policies and practices.
Despite the foregoing, the present disclosure also contemplates embodiments in which users selectively block the use of, or access to, personal information data. That is, the present disclosure contemplates that hardware and/or software elements can be provided to prevent or block access to such personal information data. For example, in the case of advertisement delivery services, the present technology can be configured to allow users to select to “opt in” or “opt out” of participation in the collection of personal information data during registration for services. In another example, users can select not to provide location information for targeted content delivery services. In yet another example, users can select to not provide precise location information, but permit the transfer of location zone information.
Therefore, although the present disclosure broadly covers use of personal information data to implement one or more various disclosed embodiments, the present disclosure also contemplates that the various embodiments can also be implemented without the need for accessing such personal information data. That is, the various embodiments of the present technology are not rendered inoperable due to the lack of all or a portion of such personal information data. For example, content can be selected and delivered to users by inferring preferences based on non-personal information data or a bare minimum amount of personal information, such as the content being requested by the device associated with a user, other non-personal information available to the content delivery services, or publically available information.
This application claims priority from U.S. Provisional Ser. No. 62/252,835, filed on Nov. 9, 2015, entitled UNCONVENTIONAL ASSISTANT INTERACTIONS, which is hereby incorporated by reference in its entirety for all purposes.
| Number | Name | Date | Kind |
|---|---|---|---|
| 7493251 | Gao et al. | Feb 2009 | B2 |
| 7529677 | Wittenber | May 2009 | B1 |
| 7568151 | Bargeron et al. | Jul 2009 | B2 |
| 7584092 | Brockett et al. | Sep 2009 | B2 |
| 7606712 | Smith et al. | Oct 2009 | B1 |
| 7607083 | Gong et al. | Oct 2009 | B2 |
| 7630900 | Strom | Dec 2009 | B1 |
| 7660715 | Thambiratnam | Feb 2010 | B1 |
| 7668710 | Doyle | Feb 2010 | B2 |
| 7673251 | Wibisono | Mar 2010 | B1 |
| 7689412 | Wu et al. | Mar 2010 | B2 |
| 7707226 | Tonse | Apr 2010 | B1 |
| 7756707 | Garner et al. | Jul 2010 | B2 |
| 7774202 | Spengler et al. | Aug 2010 | B2 |
| 7831246 | Smith et al. | Nov 2010 | B1 |
| 7869998 | Di Fabbrizio et al. | Jan 2011 | B1 |
| 7873149 | Schultz et al. | Jan 2011 | B2 |
| 7889101 | Yokota | Feb 2011 | B2 |
| 7895039 | Braho et al. | Feb 2011 | B2 |
| 7904297 | Mirkovic et al. | Mar 2011 | B2 |
| 7936863 | John et al. | May 2011 | B2 |
| 7937075 | Zellner | May 2011 | B2 |
| 7949752 | Lange et al. | May 2011 | B2 |
| 7974835 | Balchandran et al. | Jul 2011 | B2 |
| 8019604 | Ma | Sep 2011 | B2 |
| 8020104 | Robarts et al. | Sep 2011 | B2 |
| 8054180 | Scofield et al. | Nov 2011 | B1 |
| 8130929 | Wilkes et al. | Mar 2012 | B2 |
| 8140330 | Cevik et al. | Mar 2012 | B2 |
| 8145489 | Freeman et al. | Mar 2012 | B2 |
| 8160877 | Nucci et al. | Apr 2012 | B1 |
| 8175872 | Kristjansson et al. | May 2012 | B2 |
| 8175876 | Bou-Ghazale et al. | May 2012 | B2 |
| 8190596 | Nambiar et al. | May 2012 | B2 |
| 8200489 | Baggenstoss | Jun 2012 | B1 |
| 8213911 | Williams et al. | Jul 2012 | B2 |
| 8233919 | Haag et al. | Jul 2012 | B2 |
| 8234111 | Lloyd et al. | Jul 2012 | B2 |
| 8239206 | LeBeau et al. | Aug 2012 | B1 |
| 8250071 | Killalea et al. | Aug 2012 | B1 |
| 8254829 | Kindred et al. | Aug 2012 | B1 |
| 8255216 | White | Aug 2012 | B2 |
| 8260247 | Lazaridis et al. | Sep 2012 | B2 |
| 8271287 | Kermani | Sep 2012 | B1 |
| 8280438 | Barbera | Oct 2012 | B2 |
| 8300776 | Davies et al. | Oct 2012 | B2 |
| 8311189 | Champlin et al. | Nov 2012 | B2 |
| 8326627 | Kennewick et al. | Dec 2012 | B2 |
| 8332205 | Krishnan et al. | Dec 2012 | B2 |
| 8335689 | Wittenstein et al. | Dec 2012 | B2 |
| 8346563 | Hjelm et al. | Jan 2013 | B1 |
| 8370145 | Endo et al. | Feb 2013 | B2 |
| 8401163 | Kirchhoff et al. | Mar 2013 | B1 |
| 8433572 | Caskey et al. | Apr 2013 | B2 |
| 8433778 | Shreesha et al. | Apr 2013 | B1 |
| 8442821 | Vanhoucke | May 2013 | B1 |
| 8457959 | Kaiser | Jun 2013 | B2 |
| 8473289 | Jitkoff et al. | Jun 2013 | B2 |
| 8521531 | Kim | Aug 2013 | B1 |
| 8537033 | Gueziec | Sep 2013 | B2 |
| 8543375 | Hong | Sep 2013 | B2 |
| 8543397 | Nguyen | Sep 2013 | B1 |
| 8543398 | Strope et al. | Sep 2013 | B1 |
| 8583511 | Hendrickson | Nov 2013 | B2 |
| 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 |
| 8606576 | Barr et al. | Dec 2013 | B1 |
| 8638363 | King et al. | Jan 2014 | B2 |
| 8639516 | Lindahl et al. | Jan 2014 | B2 |
| 8645138 | Weinstein et al. | Feb 2014 | B1 |
| 8687777 | Lavian et al. | Apr 2014 | B1 |
| 8695074 | Saraf et al. | Apr 2014 | B2 |
| 8706474 | Blume et al. | Apr 2014 | B2 |
| 8719039 | Sharifi | May 2014 | B1 |
| 8775154 | Clinchant et al. | Jul 2014 | B2 |
| 8781456 | Prociw | Jul 2014 | B2 |
| 8798255 | Lubowich et al. | Aug 2014 | B2 |
| 8812302 | Xiao et al. | Aug 2014 | B2 |
| 8862252 | Rottler et al. | Oct 2014 | B2 |
| 8886534 | Nakano et al. | Nov 2014 | B2 |
| 8893023 | Perry et al. | Nov 2014 | B2 |
| 8898568 | Bull et al. | Nov 2014 | B2 |
| 8909693 | Frissora et al. | Dec 2014 | B2 |
| 8930176 | Li 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 |
| 8972240 | Brockett et al. | Mar 2015 | B2 |
| 8972432 | Shaw et al. | Mar 2015 | B2 |
| 8989713 | Doulton | Mar 2015 | B2 |
| 8990235 | King et al. | Mar 2015 | B2 |
| 8994660 | Neels et al. | Mar 2015 | B2 |
| 8996350 | Dub et al. | Mar 2015 | B1 |
| 8996639 | Faaborg et al. | Mar 2015 | B1 |
| 9020804 | Barbaiani et al. | Apr 2015 | B2 |
| 9026425 | Nikoulina et al. | May 2015 | B2 |
| 9031834 | Coorman et al. | May 2015 | B2 |
| 9037967 | Al-Jefri et al. | May 2015 | B1 |
| 9043208 | Koch et al. | May 2015 | B2 |
| 9049255 | MacFarlane et al. | Jun 2015 | B2 |
| 9049295 | Cooper et al. | Jun 2015 | B1 |
| 9053706 | Jitkoff et al. | Jun 2015 | B2 |
| 9058811 | Wang et al. | Jun 2015 | B2 |
| 9071701 | Donaldson et al. | Jun 2015 | B2 |
| 9076448 | Bennett et al. | Jul 2015 | B2 |
| 9076450 | Sadek et al. | Jul 2015 | B1 |
| 9082402 | Yadgar et al. | Jul 2015 | B2 |
| 9101279 | Ritchey et al. | Aug 2015 | B2 |
| 9112984 | Sejnoha et al. | Aug 2015 | B2 |
| 9164983 | Liu et al. | Oct 2015 | B2 |
| 9171541 | Kennewick et al. | Oct 2015 | B2 |
| 9171546 | Pike | Oct 2015 | B1 |
| 9190062 | Haughay | Nov 2015 | B2 |
| 9208153 | Zaveri et al. | Dec 2015 | B1 |
| 9218819 | Stekkelpak et al. | Dec 2015 | B1 |
| 9262612 | Cheyer | Feb 2016 | B2 |
| 9280535 | Varma et al. | Mar 2016 | B2 |
| 9286910 | Li et al. | Mar 2016 | B1 |
| 9292489 | Sak et al. | Mar 2016 | B1 |
| 9300718 | Khanna | Mar 2016 | B2 |
| 9325809 | Barros et al. | Apr 2016 | B1 |
| 9330659 | Ju et al. | May 2016 | B2 |
| 9330720 | Lee | May 2016 | B2 |
| 9367541 | Servan et al. | Jun 2016 | B1 |
| 9378740 | Rosen et al. | Jun 2016 | B1 |
| 9380155 | Reding et al. | Jun 2016 | B1 |
| 9383827 | Faaborg et al. | Jul 2016 | B1 |
| 9390726 | Smus et al. | Jul 2016 | B1 |
| 9396722 | Chung et al. | Jul 2016 | B2 |
| 9401147 | Jitkoff et al. | Jul 2016 | B2 |
| 9406224 | Sanders et al. | Aug 2016 | B1 |
| 9412392 | Lindahl | Aug 2016 | B2 |
| 9424840 | Hart et al. | Aug 2016 | B1 |
| 9436918 | Pantel et al. | Sep 2016 | B2 |
| 9437189 | Epstein et al. | Sep 2016 | B2 |
| 9454957 | Mathias et al. | Sep 2016 | B1 |
| 9465833 | Aravamudan et al. | Oct 2016 | B2 |
| 9466294 | Tunstall-Pedoe | Oct 2016 | B1 |
| 9471566 | Zhang et al. | Oct 2016 | B1 |
| 9484021 | Mairesse 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 |
| 9535906 | Lee et al. | Jan 2017 | B2 |
| 9536527 | Carlson | Jan 2017 | B1 |
| 9547647 | Badaskar | Jan 2017 | B2 |
| 9548050 | Gruber et al. | Jan 2017 | B2 |
| 9569549 | Jenkins et al. | Feb 2017 | B1 |
| 9575964 | Yadgar et al. | Feb 2017 | B2 |
| 9578173 | Sanghavi et al. | Feb 2017 | B2 |
| 9607612 | Deleeuw | Mar 2017 | B2 |
| 9620113 | Kennewick et al. | Apr 2017 | B2 |
| 9620126 | Chiba | Apr 2017 | B2 |
| 9626955 | Fleizach et al. | Apr 2017 | B2 |
| 9633004 | Giuli et al. | Apr 2017 | B2 |
| 9633660 | Haughay | Apr 2017 | B2 |
| 9652453 | Mathur et al. | May 2017 | B2 |
| 9658746 | Cohn et al. | May 2017 | B2 |
| 9665567 | Liu et al. | May 2017 | B2 |
| 9668121 | Naik et al. | May 2017 | B2 |
| 9672725 | Dotan-Cohen et al. | Jun 2017 | B2 |
| 9691378 | Meyers et al. | Jun 2017 | B1 |
| 9697827 | Lilly et al. | Jul 2017 | B1 |
| 9720907 | Bangalore et al. | Aug 2017 | B2 |
| 9721566 | Newendorp et al. | Aug 2017 | B2 |
| 9734839 | Adams | Aug 2017 | B1 |
| 9741343 | Miles et al. | Aug 2017 | B1 |
| 9747083 | Roman et al. | Aug 2017 | B1 |
| 9755605 | Li et al. | Sep 2017 | B1 |
| 9842584 | Hart et al. | Dec 2017 | B1 |
| 9934785 | Hulaud | Apr 2018 | B1 |
| 9948728 | Linn et al. | Apr 2018 | B2 |
| 9966068 | Cash et al. | May 2018 | B2 |
| 9967381 | Kashimba et al. | May 2018 | B1 |
| 9990176 | Gray | Jun 2018 | B1 |
| 10037758 | Jing et al. | Jul 2018 | B2 |
| 10049663 | Orr et al. | Aug 2018 | B2 |
| 10074360 | Kim | Sep 2018 | B2 |
| 10096319 | Jin et al. | Oct 2018 | B1 |
| 10102359 | Cheyer | Oct 2018 | B2 |
| 20040229569 | Franz | Nov 2004 | A1 |
| 20070043687 | Bodart | Feb 2007 | A1 |
| 20090006096 | Li et al. | Jan 2009 | A1 |
| 20090030685 | Cerra et al. | Jan 2009 | A1 |
| 20090048841 | Pollet et al. | Feb 2009 | A1 |
| 20090055380 | Peng et al. | Feb 2009 | A1 |
| 20090076798 | Oh et al. | Mar 2009 | A1 |
| 20090077047 | Cooper et al. | Mar 2009 | A1 |
| 20090077464 | Goldsmith et al. | Mar 2009 | A1 |
| 20090091537 | Huang et al. | Apr 2009 | A1 |
| 20090098903 | Donaldson et al. | Apr 2009 | A1 |
| 20090112596 | Syrdal et al. | Apr 2009 | A1 |
| 20090125602 | Bhatia et al. | May 2009 | A1 |
| 20090125813 | Shen et al. | May 2009 | A1 |
| 20090125947 | Ibaraki | May 2009 | A1 |
| 20090138263 | Shozakai et al. | May 2009 | A1 |
| 20090138430 | Nambiar et al. | May 2009 | A1 |
| 20090144036 | Jorgensen et al. | Jun 2009 | A1 |
| 20090160761 | Moosavi et al. | Jun 2009 | A1 |
| 20090163243 | Barbera | Jun 2009 | A1 |
| 20090182549 | Anisimovich et al. | Jul 2009 | A1 |
| 20090182702 | Miller | Jul 2009 | A1 |
| 20090183070 | Robbins | Jul 2009 | A1 |
| 20090190774 | Wang et al. | Jul 2009 | A1 |
| 20090192798 | Basson et al. | Jul 2009 | A1 |
| 20090204402 | Marhawa et al. | Aug 2009 | A1 |
| 20090215466 | Ahl et al. | Aug 2009 | A1 |
| 20090216528 | Gemello et al. | Aug 2009 | A1 |
| 20090219166 | MacFarlane et al. | Sep 2009 | A1 |
| 20090233264 | Rogers et al. | Sep 2009 | A1 |
| 20090234651 | Basir et al. | Sep 2009 | A1 |
| 20090248456 | Fahmy et al. | Oct 2009 | A1 |
| 20090259472 | Schroeter | Oct 2009 | A1 |
| 20090259475 | Yamagami et al. | Oct 2009 | A1 |
| 20090265171 | Davis | Oct 2009 | A1 |
| 20090274376 | Selvaraj et al. | Nov 2009 | A1 |
| 20090278804 | Rubanovich et al. | Nov 2009 | A1 |
| 20090284471 | Longe et al. | Nov 2009 | A1 |
| 20090305203 | Okumura et al. | Dec 2009 | A1 |
| 20090307594 | Kosonen et al. | Dec 2009 | A1 |
| 20090309352 | Walker et al. | Dec 2009 | A1 |
| 20090313020 | Koivunen | Dec 2009 | A1 |
| 20090319257 | Blume et al. | Dec 2009 | A1 |
| 20090319342 | Shilman et al. | Dec 2009 | A1 |
| 20100004930 | Strope et al. | Jan 2010 | A1 |
| 20100010948 | Ito et al. | Jan 2010 | A1 |
| 20100020035 | Ryu et al. | Jan 2010 | A1 |
| 20100023331 | Duta et al. | Jan 2010 | A1 |
| 20100036829 | Leyba | Feb 2010 | A1 |
| 20100036928 | Granito et al. | Feb 2010 | A1 |
| 20100057435 | Kent et al. | Mar 2010 | A1 |
| 20100057443 | Di Cristo et al. | Mar 2010 | A1 |
| 20100058200 | Jablokov et al. | Mar 2010 | A1 |
| 20100066546 | Aaron | Mar 2010 | A1 |
| 20100066684 | Shahraray et al. | Mar 2010 | A1 |
| 20100070517 | Ghosh et al. | Mar 2010 | A1 |
| 20100070521 | Clinchant et al. | Mar 2010 | A1 |
| 20100082567 | Rosenblatt et al. | Apr 2010 | A1 |
| 20100094632 | Davis et al. | Apr 2010 | A1 |
| 20100100385 | Davis et al. | Apr 2010 | A1 |
| 20100114887 | Conway et al. | May 2010 | A1 |
| 20100138798 | Wilson et al. | Jun 2010 | A1 |
| 20100145707 | Ljolje et al. | Jun 2010 | A1 |
| 20100153114 | Shih et al. | Jun 2010 | A1 |
| 20100161311 | Massuh | Jun 2010 | A1 |
| 20100161337 | Pulz et al. | Jun 2010 | A1 |
| 20100169093 | Washio | Jul 2010 | A1 |
| 20100211379 | Gorman et al. | Aug 2010 | A1 |
| 20100211644 | Lavoie et al. | Aug 2010 | A1 |
| 20100227642 | Kim et al. | Sep 2010 | A1 |
| 20100235780 | Westerman et al. | Sep 2010 | A1 |
| 20100263015 | Pandey et al. | Oct 2010 | A1 |
| 20100268537 | Al-Telmissani | Oct 2010 | A1 |
| 20100286984 | Wandinger et al. | Nov 2010 | A1 |
| 20100290632 | Lin | Nov 2010 | A1 |
| 20100318366 | Sullivan et al. | Dec 2010 | A1 |
| 20100330908 | Maddern et al. | Dec 2010 | A1 |
| 20110006876 | Moberg et al. | Jan 2011 | A1 |
| 20110015928 | Odell et al. | Jan 2011 | A1 |
| 20110016421 | Krupka et al. | Jan 2011 | A1 |
| 20110021211 | Ohki | Jan 2011 | A1 |
| 20110034183 | Haag et al. | Feb 2011 | A1 |
| 20110040707 | Theisen et al. | Feb 2011 | A1 |
| 20110047266 | Yu et al. | Feb 2011 | A1 |
| 20110047605 | Sontag et al. | Feb 2011 | A1 |
| 20110066436 | Bezar | Mar 2011 | A1 |
| 20110072033 | White et al. | Mar 2011 | A1 |
| 20110080260 | Wang et al. | Apr 2011 | A1 |
| 20110087685 | Lin et al. | Apr 2011 | A1 |
| 20110092187 | Miller | Apr 2011 | A1 |
| 20110093272 | Isobe et al. | Apr 2011 | A1 |
| 20110105097 | Tadayon et al. | May 2011 | A1 |
| 20110111724 | Baptiste | May 2011 | A1 |
| 20110112825 | Bellegarda | May 2011 | A1 |
| 20110112838 | Adibi | May 2011 | A1 |
| 20110119623 | Kim | May 2011 | A1 |
| 20110125701 | Nair et al. | May 2011 | A1 |
| 20110143726 | de Silva | Jun 2011 | A1 |
| 20110153329 | Moorer | Jun 2011 | A1 |
| 20110184736 | Slotznick | Jul 2011 | A1 |
| 20110184737 | Nakano et al. | Jul 2011 | A1 |
| 20110184768 | Norton et al. | Jul 2011 | A1 |
| 20110185288 | Gupta et al. | Jul 2011 | A1 |
| 20110191108 | Friedlander | Aug 2011 | A1 |
| 20110196670 | Dang et al. | Aug 2011 | A1 |
| 20110199312 | Okuta | Aug 2011 | A1 |
| 20110216093 | Griffin | Sep 2011 | A1 |
| 20110238191 | Kristjansson et al. | Sep 2011 | A1 |
| 20110244888 | Ohki | Oct 2011 | A1 |
| 20110257966 | Rychlik | Oct 2011 | A1 |
| 20110260829 | Lee | Oct 2011 | A1 |
| 20110264999 | Bells et al. | Oct 2011 | A1 |
| 20110276595 | Kirkland et al. | Nov 2011 | A1 |
| 20110282663 | Talwar et al. | Nov 2011 | A1 |
| 20110283189 | McCarty | Nov 2011 | A1 |
| 20110288852 | Dymetman et al. | Nov 2011 | A1 |
| 20110288855 | Roy | Nov 2011 | A1 |
| 20110288863 | Rasmussen | Nov 2011 | A1 |
| 20110288866 | Rasmussen | Nov 2011 | A1 |
| 20110302645 | Headley | Dec 2011 | A1 |
| 20110307254 | Hunt et al. | Dec 2011 | A1 |
| 20110314003 | Ju et al. | Dec 2011 | A1 |
| 20120035935 | Park et al. | Feb 2012 | A1 |
| 20120053829 | Agarwal et al. | Mar 2012 | A1 |
| 20120059813 | Sejnoha et al. | Mar 2012 | A1 |
| 20120062473 | Xiao et al. | Mar 2012 | A1 |
| 20120066212 | Jennings | Mar 2012 | A1 |
| 20120075054 | Ge et al. | Mar 2012 | A1 |
| 20120077479 | Sabotta et al. | Mar 2012 | A1 |
| 20120078611 | Soltani et al. | Mar 2012 | A1 |
| 20120078635 | Rothkopf et al. | Mar 2012 | A1 |
| 20120078747 | Chakrabarti et al. | Mar 2012 | A1 |
| 20120101823 | Weng et al. | Apr 2012 | A1 |
| 20120108166 | Hymel | May 2012 | A1 |
| 20120110456 | Larco et al. | May 2012 | A1 |
| 20120130709 | Bocchieri et al. | May 2012 | A1 |
| 20120136649 | Freising et al. | May 2012 | A1 |
| 20120136855 | Ni et al. | May 2012 | A1 |
| 20120149342 | Cohen et al. | Jun 2012 | A1 |
| 20120150544 | McLoughlin et al. | Jun 2012 | A1 |
| 20120158399 | Tremblay et al. | Jun 2012 | A1 |
| 20120173222 | Wang et al. | Jul 2012 | A1 |
| 20120173244 | Kwak et al. | Jul 2012 | A1 |
| 20120179467 | Williams | Jul 2012 | A1 |
| 20120185480 | Ni et al. | Jul 2012 | A1 |
| 20120210266 | Jiang et al. | Aug 2012 | A1 |
| 20120233207 | Mohajer | Sep 2012 | A1 |
| 20120233266 | Hassan et al. | Sep 2012 | A1 |
| 20120245939 | Braho et al. | Sep 2012 | A1 |
| 20120253785 | Hamid et al. | Oct 2012 | A1 |
| 20120253791 | Heck et al. | Oct 2012 | A1 |
| 20120259615 | Morin et al. | Oct 2012 | A1 |
| 20120262296 | Bezar | Oct 2012 | A1 |
| 20120265806 | Blanchflower et al. | Oct 2012 | A1 |
| 20120284015 | Drewes | Nov 2012 | A1 |
| 20120290291 | Shelley et al. | Nov 2012 | A1 |
| 20120296638 | Patwa | Nov 2012 | A1 |
| 20120310922 | Johnson et al. | Dec 2012 | A1 |
| 20120316862 | Sultan et al. | Dec 2012 | A1 |
| 20120316875 | Nyquist et al. | Dec 2012 | A1 |
| 20120329529 | van der Raadt | Dec 2012 | A1 |
| 20130002716 | Walker et al. | Jan 2013 | A1 |
| 20130009858 | Lacey | Jan 2013 | A1 |
| 20130010575 | He et al. | Jan 2013 | A1 |
| 20130013319 | Grant et al. | Jan 2013 | A1 |
| 20130018659 | Chi | Jan 2013 | A1 |
| 20130024576 | Dishneau et al. | Jan 2013 | A1 |
| 20130030787 | Cancedda et al. | Jan 2013 | A1 |
| 20130030789 | Dalce | 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 |
| 20130033643 | Kim et al. | Feb 2013 | A1 |
| 20130035086 | Chardon et al. | Feb 2013 | A1 |
| 20130041665 | Jang et al. | Feb 2013 | A1 |
| 20130041667 | Longe et al. | Feb 2013 | A1 |
| 20130046544 | Kay et al. | Feb 2013 | A1 |
| 20130050089 | Neels et al. | Feb 2013 | A1 |
| 20130054675 | Jenkins et al. | Feb 2013 | A1 |
| 20130063611 | Papakipos et al. | Mar 2013 | A1 |
| 20130073346 | Chun et al. | Mar 2013 | A1 |
| 20130080251 | Dempski | Mar 2013 | A1 |
| 20130082967 | Hillis et al. | Apr 2013 | A1 |
| 20130096909 | Brun et al. | Apr 2013 | A1 |
| 20130096917 | Edgar et al. | Apr 2013 | A1 |
| 20130097682 | Zeljkovic et al. | Apr 2013 | A1 |
| 20130100268 | Mihailidis et al. | Apr 2013 | A1 |
| 20130103405 | Namba et al. | Apr 2013 | A1 |
| 20130110943 | Menon et al. | May 2013 | A1 |
| 20130111365 | Chen et al. | May 2013 | A1 |
| 20130111581 | Griffin et al. | May 2013 | A1 |
| 20130132084 | Stonehocker et al. | May 2013 | A1 |
| 20130141551 | Kim | Jun 2013 | A1 |
| 20130142345 | Waldmann | Jun 2013 | A1 |
| 20130157629 | Lee et al. | Jun 2013 | A1 |
| 20130159847 | Banke et al. | Jun 2013 | A1 |
| 20130166303 | Chang et al. | Jun 2013 | A1 |
| 20130173258 | Liu et al. | Jul 2013 | A1 |
| 20130174034 | Brown et al. | Jul 2013 | A1 |
| 20130176244 | Yamamoto et al. | Jul 2013 | A1 |
| 20130179172 | Nakamura et al. | Jul 2013 | A1 |
| 20130187850 | Schulz et al. | Jul 2013 | A1 |
| 20130187857 | Griffin et al. | Jul 2013 | A1 |
| 20130204813 | Master | Aug 2013 | A1 |
| 20130204897 | McDougall | Aug 2013 | A1 |
| 20130219333 | Palwe et al. | Aug 2013 | A1 |
| 20130226935 | Bai et al. | Aug 2013 | A1 |
| 20130234947 | Kristensson et al. | Sep 2013 | A1 |
| 20130238326 | Kim et al. | Sep 2013 | A1 |
| 20130246050 | Yu et al. | Sep 2013 | A1 |
| 20130246329 | Pasquero et al. | Sep 2013 | A1 |
| 20130268263 | Park et al. | Oct 2013 | A1 |
| 20130275138 | Gruber | Oct 2013 | A1 |
| 20130275199 | Proctor, Jr. et al. | Oct 2013 | A1 |
| 20130275625 | Taivalsaari et al. | Oct 2013 | A1 |
| 20130282709 | Zhu et al. | Oct 2013 | A1 |
| 20130285913 | Griffin et al. | Oct 2013 | A1 |
| 20130291015 | Pan | Oct 2013 | A1 |
| 20130297317 | Lee et al. | Nov 2013 | A1 |
| 20130300645 | Fedorov | Nov 2013 | A1 |
| 20130300648 | Kim et al. | Nov 2013 | A1 |
| 20130303106 | Martin | Nov 2013 | A1 |
| 20130305119 | Kern et al. | Nov 2013 | A1 |
| 20130311184 | Badavne et al. | Nov 2013 | A1 |
| 20130311997 | Gruber et al. | Nov 2013 | A1 |
| 20130316746 | Miller et al. | Nov 2013 | A1 |
| 20130325967 | Parks et al. | Dec 2013 | A1 |
| 20130325970 | Roberts et al. | Dec 2013 | A1 |
| 20130331127 | Sabatelli et al. | Dec 2013 | A1 |
| 20130332159 | Federighi et al. | Dec 2013 | A1 |
| 20130332162 | Keen | Dec 2013 | A1 |
| 20130332172 | Prakash et al. | Dec 2013 | A1 |
| 20130339256 | Shroff | Dec 2013 | A1 |
| 20130346347 | Patterson et al. | Dec 2013 | A1 |
| 20140006030 | Fleizach et al. | Jan 2014 | A1 |
| 20140012574 | Pasupalak et al. | Jan 2014 | A1 |
| 20140012586 | Rubin et al. | Jan 2014 | A1 |
| 20140019460 | Sambrani et al. | Jan 2014 | A1 |
| 20140032453 | Eustice et al. | Jan 2014 | A1 |
| 20140035823 | Khoe et al. | Feb 2014 | A1 |
| 20140039893 | Weiner | Feb 2014 | A1 |
| 20140047001 | Phillips et al. | Feb 2014 | A1 |
| 20140052680 | Nitz et al. | Feb 2014 | A1 |
| 20140053210 | Cheong et al. | Feb 2014 | A1 |
| 20140067361 | Nikoulina et al. | Mar 2014 | A1 |
| 20140067402 | Kim | Mar 2014 | A1 |
| 20140074454 | Brown et al. | Mar 2014 | A1 |
| 20140074466 | Sharifi et al. | Mar 2014 | A1 |
| 20140074483 | Van Os | Mar 2014 | A1 |
| 20140079195 | Srivastava et al. | Mar 2014 | A1 |
| 20140081619 | Solntseva et al. | Mar 2014 | A1 |
| 20140088961 | Woodward et al. | Mar 2014 | A1 |
| 20140095172 | Cabaco et al. | Apr 2014 | A1 |
| 20140095173 | Lynch et al. | Apr 2014 | A1 |
| 20140096209 | Saraf et al. | Apr 2014 | A1 |
| 20140122059 | Patel et al. | May 2014 | A1 |
| 20140122136 | Jayanthi | May 2014 | A1 |
| 20140122153 | Truitt | May 2014 | A1 |
| 20140134983 | Jung et al. | May 2014 | A1 |
| 20140136987 | Rodriguez | May 2014 | A1 |
| 20140142922 | Liang et al. | May 2014 | A1 |
| 20140142935 | Lindahl et al. | May 2014 | A1 |
| 20140153709 | Byrd et al. | Jun 2014 | A1 |
| 20140156262 | Yuen et al. | Jun 2014 | A1 |
| 20140156279 | Okamoto et al. | Jun 2014 | A1 |
| 20140163953 | Parikh | Jun 2014 | A1 |
| 20140163954 | Joshi et al. | Jun 2014 | A1 |
| 20140163977 | Hoffmeister et al. | Jun 2014 | A1 |
| 20140163981 | Cook et al. | Jun 2014 | A1 |
| 20140163995 | Burns et al. | Jun 2014 | A1 |
| 20140164476 | Thomson | Jun 2014 | A1 |
| 20140164533 | Lynch et al. | Jun 2014 | A1 |
| 20140169795 | Clough | Jun 2014 | A1 |
| 20140172878 | Clark et al. | Jun 2014 | A1 |
| 20140180499 | Cooper et al. | Jun 2014 | A1 |
| 20140180697 | Torok et al. | Jun 2014 | A1 |
| 20140181865 | Koganei | Jun 2014 | A1 |
| 20140195226 | Yun et al. | Jul 2014 | A1 |
| 20140195230 | Han et al. | Jul 2014 | A1 |
| 20140195233 | Bapat | Jul 2014 | A1 |
| 20140195244 | Cha et al. | Jul 2014 | A1 |
| 20140198048 | Unruh 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 |
| 20140207466 | Smadi et al. | Jul 2014 | A1 |
| 20140207468 | Bartnik | Jul 2014 | A1 |
| 20140214429 | Pantel | Jul 2014 | A1 |
| 20140222678 | Sheets et al. | Aug 2014 | A1 |
| 20140230055 | Boehl | Aug 2014 | A1 |
| 20140244248 | Arisoy et al. | Aug 2014 | A1 |
| 20140244249 | Mohamed et al. | Aug 2014 | A1 |
| 20140244254 | Ju 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 |
| 20140244712 | Walters et al. | Aug 2014 | A1 |
| 20140245140 | Brown et al. | Aug 2014 | A1 |
| 20140249821 | Kennewick et al. | Sep 2014 | A1 |
| 20140257809 | Goel et al. | Sep 2014 | A1 |
| 20140257815 | Zhao et al. | Sep 2014 | A1 |
| 20140258857 | Dykstra-Erickson et al. | Sep 2014 | A1 |
| 20140272821 | Pitschel et al. | Sep 2014 | A1 |
| 20140274005 | Luna et al. | Sep 2014 | A1 |
| 20140278343 | Tran | Sep 2014 | A1 |
| 20140278379 | Coccaro et al. | Sep 2014 | A1 |
| 20140278390 | Kingsbury et al. | Sep 2014 | A1 |
| 20140278394 | Bastyr et al. | Sep 2014 | A1 |
| 20140278436 | Khanna et al. | Sep 2014 | A1 |
| 20140280450 | Luna | Sep 2014 | A1 |
| 20140282007 | Fleizach | Sep 2014 | A1 |
| 20140282045 | Ayanam et al. | Sep 2014 | A1 |
| 20140282201 | Pasquero et al. | Sep 2014 | A1 |
| 20140282203 | Pasquero et al. | Sep 2014 | A1 |
| 20140289508 | Wang | Sep 2014 | A1 |
| 20140297267 | Spencer et al. | Oct 2014 | A1 |
| 20140297288 | Yu et al. | Oct 2014 | A1 |
| 20140309996 | Zhang | Oct 2014 | A1 |
| 20140310001 | Kalns et al. | Oct 2014 | A1 |
| 20140310002 | Nitz et al. | Oct 2014 | A1 |
| 20140317030 | Shen | Oct 2014 | A1 |
| 20140324884 | Lindahl et al. | Oct 2014 | A1 |
| 20140330569 | Kolavennu et al. | Nov 2014 | A1 |
| 20140337371 | Li | Nov 2014 | A1 |
| 20140337438 | Govande et al. | Nov 2014 | A1 |
| 20140342762 | Hajdu et al. | Nov 2014 | A1 |
| 20140344687 | Durham et al. | Nov 2014 | A1 |
| 20140350924 | Zurek et al. | Nov 2014 | A1 |
| 20140350933 | Bak et al. | Nov 2014 | A1 |
| 20140351741 | Medlock et al. | Nov 2014 | A1 |
| 20140358523 | Sheth et al. | Dec 2014 | A1 |
| 20140361973 | Raux et al. | Dec 2014 | A1 |
| 20140365214 | Bayley | Dec 2014 | A1 |
| 20140365216 | Gruber et al. | Dec 2014 | A1 |
| 20140365226 | Sinha | Dec 2014 | A1 |
| 20140365407 | Brown 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 |
| 20140372931 | Zhai et al. | Dec 2014 | A1 |
| 20140379334 | Fry | Dec 2014 | A1 |
| 20140379341 | Seo et al. | Dec 2014 | A1 |
| 20140380285 | Gabel et al. | Dec 2014 | A1 |
| 20150006157 | Andrade Silva et al. | Jan 2015 | A1 |
| 20150006176 | Pogue et al. | Jan 2015 | A1 |
| 20150006184 | Marti et al. | Jan 2015 | A1 |
| 20150019219 | Tzirkel-Hancock et al. | Jan 2015 | A1 |
| 20150027178 | Scalisi | Jan 2015 | A1 |
| 20150031416 | Wells et al. | Jan 2015 | A1 |
| 20150033275 | Natani et al. | Jan 2015 | A1 |
| 20150039299 | Weinstein et al. | Feb 2015 | A1 |
| 20150040012 | Faaborg et al. | Feb 2015 | A1 |
| 20150045003 | Vora | Feb 2015 | A1 |
| 20150058018 | Georges et al. | Feb 2015 | A1 |
| 20150058785 | Ookawara | Feb 2015 | A1 |
| 20150066494 | Salvador et al. | Mar 2015 | A1 |
| 20150066496 | Deoras et al. | Mar 2015 | A1 |
| 20150067822 | Randall | Mar 2015 | A1 |
| 20150071121 | Patil et al. | Mar 2015 | A1 |
| 20150073788 | Allauzen et al. | Mar 2015 | A1 |
| 20150074615 | Han et al. | Mar 2015 | A1 |
| 20150082229 | Ouyang et al. | Mar 2015 | A1 |
| 20150088514 | Typrin | Mar 2015 | A1 |
| 20150088522 | Hendrickson et al. | Mar 2015 | A1 |
| 20150095278 | Flinn et al. | Apr 2015 | A1 |
| 20150100537 | Grieves et al. | Apr 2015 | A1 |
| 20150100983 | Pan | Apr 2015 | A1 |
| 20150121216 | Brown et al. | Apr 2015 | A1 |
| 20150127348 | Follis | May 2015 | A1 |
| 20150134334 | Sachidanandam et al. | May 2015 | A1 |
| 20150135123 | Carr et al. | May 2015 | A1 |
| 20150142438 | Dai et al. | May 2015 | A1 |
| 20150142851 | Gupta et al. | May 2015 | A1 |
| 20150149177 | Kalns et al. | May 2015 | A1 |
| 20150149182 | Kalns et al. | May 2015 | A1 |
| 20150154185 | Waibel | Jun 2015 | A1 |
| 20150154976 | Mutagi | Jun 2015 | A1 |
| 20150160855 | Bi | Jun 2015 | A1 |
| 20150161521 | Shah et al. | Jun 2015 | A1 |
| 20150161989 | Hsu et al. | Jun 2015 | A1 |
| 20150162001 | Kar et al. | Jun 2015 | A1 |
| 20150163558 | Wheatley | Jun 2015 | A1 |
| 20150169284 | Quast et al. | Jun 2015 | A1 |
| 20150169336 | Harper | Jun 2015 | A1 |
| 20150179176 | Ryu et al. | Jun 2015 | A1 |
| 20150185964 | Stout | Jul 2015 | A1 |
| 20150186154 | Brown et al. | Jul 2015 | A1 |
| 20150186156 | Brown et al. | Jul 2015 | A1 |
| 20150186351 | Hicks et al. | Jul 2015 | A1 |
| 20150187369 | Dadu et al. | Jul 2015 | A1 |
| 20150189362 | Lee et al. | Jul 2015 | A1 |
| 20150199077 | Zuger et al. | Jul 2015 | A1 |
| 20150199965 | Leak et al. | Jul 2015 | A1 |
| 20150199967 | Reddy et al. | Jul 2015 | A1 |
| 20150201064 | Bells et al. | Jul 2015 | A1 |
| 20150208226 | Kuusilinna | Jul 2015 | A1 |
| 20150212791 | Kumar et al. | Jul 2015 | A1 |
| 20150213796 | Waltermann et al. | Jul 2015 | A1 |
| 20150220507 | Mohajer et al. | Aug 2015 | A1 |
| 20150221304 | Stewart | Aug 2015 | A1 |
| 20150221307 | Shah et al. | Aug 2015 | A1 |
| 20150227505 | Morimoto | Aug 2015 | A1 |
| 20150230095 | Smith et al. | Aug 2015 | A1 |
| 20150242091 | Lu et al. | Aug 2015 | A1 |
| 20150243283 | Halash et al. | Aug 2015 | A1 |
| 20150248886 | Sarikaya 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 |
| 20150261850 | Mittal | Sep 2015 | A1 |
| 20150269139 | McAteer et al. | Sep 2015 | A1 |
| 20150277574 | Jain et al. | Oct 2015 | A1 |
| 20150279358 | Kingsbury et al. | Oct 2015 | A1 |
| 20150281380 | Wang et al. | Oct 2015 | A1 |
| 20150286627 | Chang et al. | Oct 2015 | A1 |
| 20150287401 | Lee et al. | Oct 2015 | A1 |
| 20150288629 | Choi et al. | Oct 2015 | A1 |
| 20150294086 | Kare et al. | Oct 2015 | A1 |
| 20150294377 | Chow | Oct 2015 | A1 |
| 20150295915 | Xiu | Oct 2015 | A1 |
| 20150302855 | Kim et al. | Oct 2015 | A1 |
| 20150302856 | Kim et al. | Oct 2015 | A1 |
| 20150302857 | Yamada | Oct 2015 | A1 |
| 20150310858 | Li et al. | Oct 2015 | A1 |
| 20150310862 | Dauphin et al. | Oct 2015 | A1 |
| 20150310879 | Buchanan et al. | Oct 2015 | A1 |
| 20150317069 | Clements et al. | Nov 2015 | A1 |
| 20150317310 | Eiche et al. | Nov 2015 | A1 |
| 20150319411 | Kasmir et al. | Nov 2015 | A1 |
| 20150331664 | Osawa et al. | Nov 2015 | A1 |
| 20150332667 | Mason | Nov 2015 | A1 |
| 20150340033 | Di Fabbrizio et al. | Nov 2015 | A1 |
| 20150341717 | Song et al. | Nov 2015 | A1 |
| 20150347086 | Liedholm et al. | Dec 2015 | A1 |
| 20150347381 | Bellegarda | Dec 2015 | A1 |
| 20150347385 | Flor et al. | Dec 2015 | A1 |
| 20150347733 | Tsou et al. | Dec 2015 | A1 |
| 20150347985 | Gross et al. | Dec 2015 | A1 |
| 20150348549 | Giuli | Dec 2015 | A1 |
| 20150348554 | Orr et al. | Dec 2015 | A1 |
| 20150352999 | Bando et al. | Dec 2015 | A1 |
| 20150355879 | Beckhardt et al. | Dec 2015 | A1 |
| 20150363587 | Ahn et al. | Dec 2015 | A1 |
| 20150364140 | Thorn | Dec 2015 | A1 |
| 20150371639 | Foerster et al. | Dec 2015 | A1 |
| 20150371665 | Naik et al. | Dec 2015 | A1 |
| 20150373183 | Woolsey et al. | Dec 2015 | A1 |
| 20150382047 | Napolitano et al. | Dec 2015 | A1 |
| 20150382079 | Lister et al. | Dec 2015 | A1 |
| 20160004690 | Bangalore et al. | Jan 2016 | A1 |
| 20160005320 | deCharms et al. | Jan 2016 | A1 |
| 20160012038 | Edwards et al. | Jan 2016 | A1 |
| 20160014476 | Caliendo, Jr. et al. | Jan 2016 | A1 |
| 20160018900 | Tu et al. | Jan 2016 | A1 |
| 20160019886 | Hong | Jan 2016 | A1 |
| 20160026258 | Ou et al. | Jan 2016 | A1 |
| 20160029316 | Mohan et al. | Jan 2016 | A1 |
| 20160034042 | Joo | Feb 2016 | A1 |
| 20160048666 | Dey et al. | Feb 2016 | A1 |
| 20160062605 | Agarwal et al. | Mar 2016 | A1 |
| 20160070581 | Soon-Shiong | Mar 2016 | A1 |
| 20160071516 | Lee et al. | Mar 2016 | A1 |
| 20160071521 | Haughay | Mar 2016 | A1 |
| 20160072940 | Cronin | Mar 2016 | A1 |
| 20160078860 | Paulik et al. | Mar 2016 | A1 |
| 20160092766 | Sainath et al. | Mar 2016 | A1 |
| 20160093301 | Bellegarda et al. | Mar 2016 | A1 |
| 20160094700 | Lee et al. | Mar 2016 | A1 |
| 20160098991 | Luo et al. | Apr 2016 | A1 |
| 20160104486 | Penilla et al. | Apr 2016 | A1 |
| 20160111091 | Bakish | Apr 2016 | A1 |
| 20160117386 | Ajmera et al. | Apr 2016 | A1 |
| 20160118048 | Heide | Apr 2016 | A1 |
| 20160125048 | Hamada | May 2016 | A1 |
| 20160125071 | Gabbai | May 2016 | A1 |
| 20160132484 | Nauze | May 2016 | A1 |
| 20160132488 | Clark et al. | May 2016 | A1 |
| 20160133254 | Vogel et al. | May 2016 | A1 |
| 20160139662 | Dabhade | May 2016 | A1 |
| 20160140951 | Agiomyrgiannakis et al. | May 2016 | A1 |
| 20160148610 | Kennewick, Jr. et al. | May 2016 | A1 |
| 20160155443 | Khan 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 |
| 20160170966 | Kolo | Jun 2016 | A1 |
| 20160173578 | Sharma et al. | Jun 2016 | A1 |
| 20160173960 | Snibbe et al. | Jun 2016 | A1 |
| 20160179462 | Bjorkengren | 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 |
| 20160198319 | Huang et al. | Jul 2016 | A1 |
| 20160210981 | Lee | Jul 2016 | A1 |
| 20160217784 | Gelfenbeyn et al. | Jul 2016 | A1 |
| 20160224540 | Stewart et al. | Aug 2016 | A1 |
| 20160224774 | Pender | Aug 2016 | A1 |
| 20160247061 | Trask 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 | Labsk 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 |
| 20160266871 | Schmid et al. | Sep 2016 | A1 |
| 20160267904 | Biadsy et al. | Sep 2016 | A1 |
| 20160275947 | Li et al. | Sep 2016 | A1 |
| 20160282956 | Ouyang et al. | Sep 2016 | A1 |
| 20160284005 | Daniel et al. | Sep 2016 | A1 |
| 20160284199 | Dotan-Cohen et al. | Sep 2016 | A1 |
| 20160286045 | Shaltiel et al. | Sep 2016 | A1 |
| 20160293168 | Chen | Oct 2016 | A1 |
| 20160299685 | Zhai et al. | Oct 2016 | A1 |
| 20160299882 | Hegerty et al. | Oct 2016 | A1 |
| 20160299883 | Zhu et al. | Oct 2016 | A1 |
| 20160307566 | Bellegarda | Oct 2016 | A1 |
| 20160313906 | Kilchenko et al. | Oct 2016 | A1 |
| 20160314788 | Jitkoff et al. | Oct 2016 | A1 |
| 20160314792 | Alvarez et al. | Oct 2016 | A1 |
| 20160321261 | Spasojevic et al. | Nov 2016 | A1 |
| 20160322045 | Hatfeild et al. | Nov 2016 | A1 |
| 20160322050 | Wang et al. | Nov 2016 | A1 |
| 20160328205 | Agrawal et al. | Nov 2016 | A1 |
| 20160328893 | Cordova et al. | Nov 2016 | A1 |
| 20160336007 | Hanazawa | Nov 2016 | A1 |
| 20160336010 | Lindahl | Nov 2016 | A1 |
| 20160336024 | Choi et al. | Nov 2016 | A1 |
| 20160337299 | Lane et al. | Nov 2016 | A1 |
| 20160337301 | Rollins et al. | Nov 2016 | A1 |
| 20160342685 | Basu | Nov 2016 | A1 |
| 20160342781 | Jeon | Nov 2016 | A1 |
| 20160351190 | Binder et al. | Dec 2016 | A1 |
| 20160352567 | Robbins et al. | Dec 2016 | A1 |
| 20160357304 | Hatori et al. | Dec 2016 | A1 |
| 20160357728 | Bellegarda 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 |
| 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 |
| 20160365101 | Foy et al. | Dec 2016 | A1 |
| 20160371250 | Rhodes | Dec 2016 | A1 |
| 20160372112 | Miller et al. | Dec 2016 | A1 |
| 20160378747 | Orr et al. | Dec 2016 | A1 |
| 20160379091 | Lin et al. | Dec 2016 | A1 |
| 20160379626 | Deisher et al. | Dec 2016 | A1 |
| 20160379633 | Lehman et al. | Dec 2016 | A1 |
| 20160379641 | Liu et al. | Dec 2016 | A1 |
| 20170004824 | Yoo et al. | Jan 2017 | A1 |
| 20170011303 | Annapureddy et al. | Jan 2017 | A1 |
| 20170011742 | Jing et al. | Jan 2017 | A1 |
| 20170018271 | Khan et al. | Jan 2017 | A1 |
| 20170019987 | Dragone et al. | Jan 2017 | A1 |
| 20170025124 | Mixter et al. | Jan 2017 | A1 |
| 20170031576 | Saoji et al. | Feb 2017 | A1 |
| 20170032783 | Lord et al. | Feb 2017 | A1 |
| 20170032791 | Elson et al. | Feb 2017 | A1 |
| 20170040002 | Basson et al. | Feb 2017 | A1 |
| 20170055895 | Des Jardins et al. | Mar 2017 | A1 |
| 20170060853 | Lee 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 |
| 20170076720 | Gopalan et al. | Mar 2017 | A1 |
| 20170076721 | Bargetzi et al. | Mar 2017 | A1 |
| 20170083179 | Gruber et al. | Mar 2017 | A1 |
| 20170083285 | Meyers et al. | Mar 2017 | A1 |
| 20170090569 | Levesque | Mar 2017 | A1 |
| 20170091168 | Bellegarda et al. | Mar 2017 | A1 |
| 20170092270 | Newendorp et al. | Mar 2017 | A1 |
| 20170092278 | Evermann et al. | Mar 2017 | A1 |
| 20170102915 | Kuscher et al. | Apr 2017 | A1 |
| 20170103749 | Zhao et al. | Apr 2017 | A1 |
| 20170105190 | Logan et al. | Apr 2017 | A1 |
| 20170116177 | Walia | Apr 2017 | A1 |
| 20170116989 | Yadgar et al. | Apr 2017 | A1 |
| 20170124190 | Wang et al. | May 2017 | A1 |
| 20170125016 | Wang | May 2017 | A1 |
| 20170127124 | Wilson et al. | May 2017 | A9 |
| 20170131778 | Iyer | May 2017 | A1 |
| 20170140644 | Hwang et al. | May 2017 | A1 |
| 20170154033 | Lee | Jun 2017 | A1 |
| 20170154055 | Dimson et al. | Jun 2017 | A1 |
| 20170161018 | Lemay et al. | Jun 2017 | A1 |
| 20170161268 | Badaskar | Jun 2017 | A1 |
| 20170169818 | VanBlon et al. | Jun 2017 | A1 |
| 20170169819 | Mese et al. | Jun 2017 | A1 |
| 20170178619 | Naik et al. | Jun 2017 | A1 |
| 20170178626 | Gruber et al. | Jun 2017 | A1 |
| 20170180499 | Gelfenbeyn et al. | Jun 2017 | A1 |
| 20170185375 | Martel et al. | Jun 2017 | A1 |
| 20170185581 | Bojja et al. | Jun 2017 | A1 |
| 20170186429 | Giuli et al. | Jun 2017 | A1 |
| 20170193083 | Bhatt et al. | Jul 2017 | A1 |
| 20170199874 | Patel et al. | Jul 2017 | A1 |
| 20170200066 | Wang et al. | Jul 2017 | A1 |
| 20170221486 | Kurata et al. | Aug 2017 | A1 |
| 20170227935 | Su et al. | Aug 2017 | A1 |
| 20170228382 | Haviv et al. | Aug 2017 | A1 |
| 20170230709 | Van Os et al. | Aug 2017 | A1 |
| 20170242653 | Lang et al. | Aug 2017 | A1 |
| 20170243468 | Dotan-Cohen et al. | Aug 2017 | A1 |
| 20170256256 | Wang 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 |
| 20170264451 | Yu et al. | Sep 2017 | A1 |
| 20170278514 | Mathias et al. | Sep 2017 | A1 |
| 20170285915 | Napolitano et al. | Oct 2017 | A1 |
| 20170286397 | Gonzalez | Oct 2017 | A1 |
| 20170295446 | Thagadur Shivappa | Oct 2017 | A1 |
| 20170316775 | Le et al. | Nov 2017 | A1 |
| 20170316782 | Haughay et al. | Nov 2017 | A1 |
| 20170323637 | Naik | Nov 2017 | A1 |
| 20170345411 | Raitio et al. | Nov 2017 | A1 |
| 20170346949 | Sanghavi et al. | Nov 2017 | A1 |
| 20170352346 | Paulik et al. | Dec 2017 | A1 |
| 20170352350 | Booker et al. | Dec 2017 | A1 |
| 20170357478 | Piersol 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, II et al. | Dec 2017 | A1 |
| 20170358304 | Castillo et al. | Dec 2017 | A1 |
| 20170358305 | Kudurshian et al. | Dec 2017 | A1 |
| 20170371885 | Aggarwal et al. | Dec 2017 | A1 |
| 20180007060 | Leblang et al. | Jan 2018 | A1 |
| 20180007538 | Naik et al. | Jan 2018 | A1 |
| 20180012596 | Piernot et al. | Jan 2018 | A1 |
| 20180033431 | Newendorp et al. | Feb 2018 | A1 |
| 20180054505 | Hart et al. | Feb 2018 | A1 |
| 20180060312 | Won | Mar 2018 | A1 |
| 20180063624 | Boesen | Mar 2018 | A1 |
| 20180067914 | Chen et al. | Mar 2018 | A1 |
| 20180090143 | Saddler et al. | Mar 2018 | A1 |
| 20180107945 | Gao et al. | Apr 2018 | A1 |
| 20180108346 | Paulik et al. | Apr 2018 | A1 |
| 20180130470 | Lemay et al. | May 2018 | A1 |
| 20180137856 | Gilbert | May 2018 | A1 |
| 20180137857 | Zhou et al. | May 2018 | A1 |
| 20180144748 | Leong | May 2018 | A1 |
| 20180190273 | Karimli et al. | Jul 2018 | A1 |
| 20180196683 | Radebaugh et al. | Jul 2018 | A1 |
| 20180213448 | Segal et al. | Jul 2018 | A1 |
| 20180218735 | Hunt et al. | Aug 2018 | A1 |
| 20180308485 | Kudurshian et al. | Oct 2018 | A1 |
| 20180308486 | Saddler et al. | Oct 2018 | A1 |
| 20180322112 | Bellegarda 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 |
| 20180330714 | Paulik et al. | Nov 2018 | A1 |
| 20180330723 | Acero et al. | Nov 2018 | A1 |
| 20180330730 | Garg et al. | Nov 2018 | A1 |
| 20180330731 | Zeitlin et al. | Nov 2018 | A1 |
| 20180330737 | Paulik et al. | Nov 2018 | A1 |
| 20180332118 | Phipps et al. | Nov 2018 | A1 |
| 20180336275 | Graham et al. | Nov 2018 | A1 |
| 20180336894 | Graham et al. | Nov 2018 | A1 |
| 20180336905 | Kim et al. | Nov 2018 | A1 |
| Number | Date | Country |
|---|---|---|
| 2015203483 | Jul 2015 | AU |
| 2015101171 | Oct 2015 | AU |
| 101416471 | Apr 2009 | CN |
| 101448340 | Jun 2009 | CN |
| 101453498 | Jun 2009 | CN |
| 101499156 | Aug 2009 | CN |
| 101500041 | Aug 2009 | CN |
| 101515952 | Aug 2009 | CN |
| 101547396 | Sep 2009 | CN |
| 101557432 | Oct 2009 | CN |
| 101601088 | Dec 2009 | CN |
| 101604521 | Dec 2009 | CN |
| 101751387 | Jun 2010 | CN |
| 101833286 | Sep 2010 | CN |
| 102137193 | Jul 2011 | CN |
| 102201235 | Sep 2011 | CN |
| 102282609 | Dec 2011 | CN |
| 102368256 | Mar 2012 | CN |
| 102405463 | Apr 2012 | CN |
| 102498457 | Jun 2012 | CN |
| 102629246 | Aug 2012 | CN |
| 102682769 | Sep 2012 | CN |
| 102682771 | Sep 2012 | CN |
| 102685295 | Sep 2012 | CN |
| 102693725 | Sep 2012 | CN |
| 102792320 | Nov 2012 | CN |
| 102801853 | Nov 2012 | CN |
| 102870065 | Jan 2013 | CN |
| 102917004 | Feb 2013 | CN |
| 102918493 | Feb 2013 | CN |
| 103038728 | Apr 2013 | CN |
| 103093334 | May 2013 | CN |
| 103135916 | Jun 2013 | CN |
| 103365279 | Oct 2013 | CN |
| 103744761 | Apr 2014 | CN |
| 103795850 | May 2014 | CN |
| 103930945 | Jul 2014 | CN |
| 104038621 | Sep 2014 | CN |
| 104090652 | Oct 2014 | CN |
| 104144377 | Nov 2014 | CN |
| 104284257 | Jan 2015 | CN |
| 104423625 | Mar 2015 | CN |
| 104463552 | Mar 2015 | CN |
| 104516522 | Apr 2015 | CN |
| 104854583 | Aug 2015 | CN |
| 104951077 | Sep 2015 | CN |
| 105247511 | Jan 2016 | CN |
| 105264524 | Jan 2016 | CN |
| 105471705 | Apr 2016 | CN |
| 107919123 | Apr 2018 | CN |
| 202016008226 | May 2017 | DE |
| 2081185 | Jul 2009 | EP |
| 2096840 | Sep 2009 | EP |
| 2329348 | Jun 2011 | EP |
| 2339576 | Jun 2011 | EP |
| 2523188 | Nov 2012 | EP |
| 2632129 | Aug 2013 | EP |
| 2669889 | Dec 2013 | EP |
| 2683175 | Jan 2014 | EP |
| 2760015 | Jul 2014 | EP |
| 2849177 | Mar 2015 | EP |
| 2930715 | Oct 2015 | EP |
| 2950307 | Dec 2015 | EP |
| 3035329 | Jun 2016 | EP |
| 3224708 | Oct 2017 | EP |
| 3246916 | Nov 2017 | EP |
| 3300074 | Mar 2018 | EP |
| 2983065 | Aug 2018 | EP |
| 2009-2850 | Jan 2009 | JP |
| 2009-505142 | Feb 2009 | JP |
| 2009-69062 | Apr 2009 | JP |
| 2009-110300 | May 2009 | JP |
| 2009-134409 | Jun 2009 | JP |
| 2009-223840 | Oct 2009 | JP |
| 2009-543166 | Dec 2009 | JP |
| 2010-518475 | May 2010 | JP |
| 2010-146347 | Jul 2010 | JP |
| 2010-166478 | Jul 2010 | JP |
| 2010-205111 | Sep 2010 | JP |
| 2011-33874 | Feb 2011 | JP |
| 2011-250027 | Dec 2011 | JP |
| 2012-33997 | Feb 2012 | JP |
| 2012-508530 | Apr 2012 | JP |
| 2012-89020 | May 2012 | JP |
| 2012-116442 | Jun 2012 | JP |
| 2012-142744 | Jul 2012 | JP |
| 2012-518847 | Aug 2012 | JP |
| 2013-37688 | Feb 2013 | JP |
| 2013-65284 | Apr 2013 | JP |
| 2013-513315 | Apr 2013 | JP |
| 2013-80476 | May 2013 | JP |
| 2013-140520 | Jul 2013 | JP |
| 2013-528012 | Jul 2013 | JP |
| 2013-156349 | Aug 2013 | JP |
| 2013-200423 | Oct 2013 | JP |
| 2013-205999 | Oct 2013 | JP |
| 2013-238936 | Nov 2013 | JP |
| 2014-10688 | Jan 2014 | JP |
| 2014-26629 | Feb 2014 | JP |
| 2014-60600 | Apr 2014 | JP |
| 2014-72586 | Apr 2014 | JP |
| 2014-109889 | Jun 2014 | JP |
| 2014-124332 | Jul 2014 | JP |
| 2014-145842 | Aug 2014 | JP |
| 2014-150323 | Aug 2014 | JP |
| 2014-222514 | Nov 2014 | JP |
| 2015-8001 | Jan 2015 | JP |
| 2015-501022 | Jan 2015 | JP |
| 2015-41845 | Mar 2015 | JP |
| 2015-94848 | May 2015 | JP |
| 2015-519675 | Jul 2015 | JP |
| 2015-524974 | Aug 2015 | JP |
| 2015-526776 | Sep 2015 | JP |
| 2015-528140 | Sep 2015 | JP |
| 2015-528918 | Oct 2015 | JP |
| 2016-119615 | Jun 2016 | JP |
| 10-2010-0053149 | May 2010 | KR |
| 10-2011-0086492 | Jul 2011 | KR |
| 10-2011-0100620 | Sep 2011 | KR |
| 10-1178310 | Aug 2012 | KR |
| 10-2012-0137440 | Dec 2012 | KR |
| 10-2012-0139827 | Dec 2012 | KR |
| 10-2013-0035983 | Apr 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 |
| 10-2014-0031283 | Mar 2014 | KR |
| 10-2014-0033574 | Mar 2014 | KR |
| 10-2014-0147557 | Dec 2014 | KR |
| 10-2015-0043512 | Apr 2015 | KR |
| 10-2016-0010523 | Jan 2016 | KR |
| 201142823 | Dec 2011 | TW |
| 2009034686 | Mar 2009 | WO |
| 2010100937 | Sep 2010 | WO |
| 2011088053 | Jan 2012 | WO |
| 2012019637 | Feb 2012 | WO |
| 2013009578 | Jan 2013 | WO |
| 2013022223 | Feb 2013 | WO |
| 2013049358 | Apr 2013 | WO |
| 2013163113 | Oct 2013 | WO |
| 2013173504 | Nov 2013 | WO |
| 2013176847 | Nov 2013 | WO |
| 2013184990 | Dec 2013 | WO |
| 2014003138 | Jan 2014 | WO |
| 2014021967 | Feb 2014 | WO |
| 2014022148 | Feb 2014 | WO |
| 2014047047 | Mar 2014 | WO |
| 2014070872 | May 2014 | WO |
| 2014096506 | Jun 2014 | WO |
| 2014124332 | Aug 2014 | WO |
| 2014137074 | Sep 2014 | WO |
| 2014138604 | Sep 2014 | WO |
| 2014169269 | Oct 2014 | WO |
| 2014200728 | Dec 2014 | WO |
| 2015018440 | Feb 2015 | WO |
| 2015029379 | Mar 2015 | WO |
| 2015092943 | Jun 2015 | WO |
| 2015094169 | Jun 2015 | WO |
| 2015094369 | Jun 2015 | WO |
| 2015099939 | Jul 2015 | WO |
| 2015116151 | Aug 2015 | WO |
| 2015151133 | Oct 2015 | WO |
| 2015157013 | Oct 2015 | WO |
| 2015183699 | Dec 2015 | WO |
| 2015184186 | Dec 2015 | WO |
| 2015200207 | Dec 2015 | WO |
| 2016027933 | Feb 2016 | WO |
| 2016028946 | Feb 2016 | WO |
| 2016033257 | Mar 2016 | WO |
| 2016054230 | Apr 2016 | WO |
| 2016057268 | Apr 2016 | WO |
| 2016075081 | May 2016 | WO |
| 2016085775 | Jun 2016 | WO |
| 2016100139 | Jun 2016 | WO |
| 2016111881 | Jul 2016 | WO |
| 2016144840 | Sep 2016 | WO |
| 2016144982 | Sep 2016 | WO |
| 2016175354 | Nov 2016 | WO |
| 2016209444 | Dec 2016 | WO |
| 2017044260 | Mar 2017 | WO |
| 2017044629 | Mar 2017 | WO |
| 2017053311 | Mar 2017 | WO |
| Entry |
|---|
| International Preliminary Report on Patentability received for PCT Patent Application No. PCT/US2016/051151, dated Mar. 13, 2018, 17 pages. |
| International Search Report and Written Opinion Received for PCT Patent Application No. PCT/US2016/051151, dated Nov. 22, 2016, 10 pages. |
| Extended European Search Report received for European Patent Application No. 16864716.2, dated Feb. 21, 2019, 12 pages. |
| Wikipedia, “Home Automation”, Available at: <https://en.wikipedia.org/w/index.php?title=Home_automation&oldid=686569068>, Oct. 19, 2015, 9 Pages. |
| Wikipedia, “Siri”, 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. |
| Office Action received for European Patent Application No. 16864716.2, dated Nov. 26, 2019, 12 pages. |
| Bell, Jason, “Machine Learning Hands-On for Developers and Technical Professionals”, Wiley, 2014, 82 pages. |
| Coulouris, et al., “Distributed Systems: Concepts and Design (Fifth Edition)”, Addison-Wesley, 2011, 391 pages. |
| Gupta, Naresh, “Inside Bluetooth Low Energy”, Artech House, 2013, 274 pages. |
| Hutsko, et al., “iPhone All-in-One for Dummies”, 3rd Edition, 2013, 98 pages. |
| Jefford, et al., “Professional BizTalk Server 2006”, Wrox, 2007, 398 pages. |
| 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. |
| Rowland, et al., “Designing Connected Products: UX for the Consumer Internet of Things”, O'Reilly, May 2015, 452 pages. |
| Seroter, et al., “SOA Patterns with BizTalk Server 2013 and Microsoft Azure”, Packt Publishing, Jun. 2015, 454 pages. |
| Asakura et al., “What LG thinks; How the TV should be in the Living Room”, HiVi, vol. 31, No. 7 (Jul. 2013), Stereo Sound Publishing, Inc., Jun. 17, 2013, pp. 68-71 (Official Copy Only) (See Communication under 37 CFR § 1.98(a) (3)). |
| Ashbrook, Daniel L.., “Enabling Mobile Microinteractions”, Retrieved from the Internet: URL: “http://danielashbrook.com/wp-content/uploads/2012/06/2009-Ashbrook-Thesis.pdf”, May 2010, 186 pages. |
| Ashingtondctech & Gaming, “SwipeStatusBar—Reveal the Status Bar in a Fullscreen App”, Online Available at: <https://www.youtube.com/watch?v=wA_T9lAreQ>, Jul. 1, 2013, 3 pages. |
| “Ask Alexa—Things That Are Smart Wiki”, Available online at <URL:http://thingsthataresmart.wiki/index.php?title=Ask_Alexa&oldid=4283>, [retrieved from internet on Aug. 2, 2017], Jun. 8, 2016; pp. 1-31. |
| 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. |
| “DIRECTV™ Voice”, Now Part of the DIRECTTV Mobile App for Phones, Sep. 18, 2013, 5 pages. |
| EARTHLING1984, “Samsung Galaxy Smart Stay Feature Explained”, Available online at:- “https://www.youtube.com/watch?v=RpjBNtSjupl”, May 29, 2013, 1 page. |
| Filipowicz, Luke, “How to use the Quick Type Keyboard in iOS 8”, available online at <https://www.imore.com/comment/568232>, Oct. 11, 2014, pp. 1-17. |
| Finkel et al., “Joint Parsing and Named Entity Recognition”, Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the ACL, Jun. 2009, pp. 326-334. |
| “Galaxy S7: How to Adjust Screen Timeout & Lock Screen Timeout”, Available online at:- “https://www.youtube.com/watch?v=n6e1WKUS2ww”, Jun. 9, 2016, 1 page. |
| Google Developers, “Voice Search in Your App”, Available online at:- https://www.youtube.com/watch?v=PS1FbB5qWEI, Nov. 12, 2014, 1 page. |
| “Hey Google: How to Create a Shopping List with Your Google Assistant”, Available online at:- https://www.youtube.com/watch?v=w9NCsElax1Y, May 25, 2018, 1 page. |
| “How to Enable Google Assistant on Galaxy 57 and other Android Phones (No Root)”, Available online at:- “https://www.youtube.com/watch?v=HeklQbWyksE”, Mar. 20, 2017, 1 page. |
| “How to Use Ok Google Assistant Even Phone is Locked”, Available online at:- “https://www.youtube.com/watch?v=9B_gP4j_SP8”, Mar. 12, 2018, 1 page. |
| INEWS and Tech, “How to Use the QuickType Keyboard in iOS 8”, Available online at: - “http://www.inewsandtech.com/how-to-use-the-quicktype-keyboard-in-ios-81”, Sep. 17, 2014, 6 pages. |
| IOS 8 Release, “Quick Type Keyboard on iOS 8 Makes Typing Easier”, Retrieved from the Internet: URL:https://www.youtube.com/watch?v=0CidLR4fhVU, [Retrieved on Nov. 23, 2018], XP054978896, Jun. 3, 2014, 1 page. |
| Jonsson et al, “Proximity-based Reminders Using Bluetooth”, 2014 IEEE International Conference on Pervasive Computing and Communications Demonstrations, 2014, pp. 151-153. |
| Karn, Ujjwal, “An Intuitive Explanation of Convolutional Neural Networks”, The Data Science Blog, Aug. 11, 2016, 23 pages. |
| Liou et al., “Autoencoder for Words”, Neurocomputing, vol. 139, Sep. 2014, pp. 84-96. |
| Majerus, Wesley, “Cell Phone Accessibility for your Blind Child”, Retrieved from the Internet URL:https://web.archive.org/web/20100210001100/https://nfb.org/images/nfb/publications/fr/fr28/3/fr280314.htm, 2010, pp. 1-5. |
| Marketing Land, “Amazon Echo: Play Music”, Online Available at: <https://www.youtube.com/watch?v=A7V5NPbsXi4>, Apr. 27, 2015, 3 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. |
| Morrison, Jonathan, “iPhone 5 Siri Demo”, Online Available at <https://www.youtube.com/watch?v=_wHWwG5IhWc>, Sep. 21, 2012, 3 pages. |
| Nakamura, Satoshi, “Overcoming the Language Barrier with Speech Translation Technology, Science & Technology Trends”, Quarterly Review No. 31, Apr. 2009, pp. 36-49. |
| Nakazawa et al., “Detection and Labeling of Significant Scenes from TV program based on Twitter Analysis”, Proceedings of the 3rd Forum on Data Engineering and Information Management (Deim 2011 proceedings), IEICE Data Engineering Technical Group. Available online at: http://db-event.jpn.org/deim2011/proceedings/pdf/f5-6.pdf, Feb. 28, 2011, 10 pages (Official Copy Only) (See Communication under 37 CFR § 1.98(a) (3)). |
| Nozawa et al., “iPhone 4S Perfect Manual”, vol. 1, First Edition, Nov. 11, 2011, 4 pages (Official Copy Only) (See Communication under 37 CFR § 1.98(a) (3)). |
| Okuno et al., “System for Japanese Input Method based on the Internet”, Technical Report of Information Processing Society of Japan, Natural Language Processing, Japan, Information Processing Society of Japan, vol. 2009, No. 36, Mar. 18, 2009, 8 pages (Official Copy Only) (See Communication under 37 CFR § 1.98(a) (3)). |
| Patra et al., “A Kernel-Based Approach for Biomedical Named Entity Recognition”, Scientific World Journal, vol. 2013, 2013, pp. 1-7. |
| Pennington et al., “GloVe: Global Vectors for Word Representation”, Proceedings of the Conference on Empirical Methods Natural Language Processing (EMNLP), 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. |
| Samsung, “SGH-a885 Series—Portable Quad-Band Mobile Phone—User Manual”, Retrieved from the Internet: URL: “http://web.archive.org/web/20100106113758/http://www.comparecellular.com/images/phones/userguide1896.pdf”, Jan. 1, 2009, 144 pages. |
| Seehafer, Brent, “Activate google assistant on Galaxy S7 with screen off”, Available online at:- “https://productforums.google.com/forum/#!topic/websearch/lp3qlGBHLVI”, 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. |
| Spivack, Nova, “Sneak Preview of Siri—Part Two—Technical Foundations—Interview with Tom Gruber, CTO of Siri”, Online Available at <https://web.archive.org/web/20100114234454/http://www.twine.com/item/12vhy39k4-22m/interview-with-tom-gruber-of-siri>, Jan. 14, 2010, 5 pages. |
| Sundermeyer et al., “From Feedforward to Recurrent LSTM Neural Networks for Language Modeling”, IEEE Transactions to Audio, Speech, and Language Processing, 2015, vol. 23, Mar. 2015, pp. 517-529. |
| Sundermeyer et al., “LSTM Neural Networks for Language Modeling”, INTERSPEECH 2012, ISCA's 13 Annual Conference, Sep. 9-13, 2012, pp. 194-197. |
| Tanaka, Tatsuo, “Next Generation IT Channel Strategy Through “Experience Technology””, Intellectual Resource Creation, Japan, Nomura Research Institute Ltd. vol. 19, No. 1, Dec. 20, 2010, 17 pages. (Official Copy only) (See Communication under 37 CFR § 1.98(a) (3)). |
| “The world of Virtual Assistants—more SemTech . . . ”, End of Business as Usual—Glenn's External blog. Online Available at <https://web.archive.org/web/20091101840940/http://glennas.wordpress.com/2009/10/17/the-world-of-virtual-assistants-more-semtech/>, Oct. 17, 2009, 5 pages. |
| Vodafone Deutschland, “Samsung Galaxy S3 Tastatur Spracheingabe”, Available online at—“https://www.youtube.com/watch?v=6kOd6Gr8uFE”, Aug. 22, 2012, 1 page. |
| X.Ai, “How it Works”, Available online at: https://web.archive.org/web/20160531201426/https://x.ai/how-it-works/, May 31, 2016, 6 pages. |
| Xu, Yuhong, “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. |
| Yan et al., “A Scalable Approach to Using DNN-Derived Features in GMM-HMM Based Acoustic Modeling for LVCSR”, In Interspeech, 2013, pp. 104-108. |
| Yates, Michael C., “How can I exit Google Assistant after i'm finished with it”, Available online at:- “https://productforums.google.com/forum/#!msg/phone-by-google/faECnR2RJwA/gKNtOkQgAQAJ”, Jan. 11, 2016, 2 pages. |
| Young et al., “The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management”, Computer Speech & Language, vol. 24, Issue 2, 2010, pp. 150-174. |
| Zangerle et al., “Recommending #-Tag in Twitter”, Proceedings of the Workshop on Semantic Adaptive Social Web, 2011, pp. 1-12. |
| Summons to Attend Oral Proceedings received for European Patent Application No. 16864716.2, dated Jul. 17, 2020, 12 pages. |
| Result of Consultation received for European Patent Application No. 16864716.2, dated Oct. 28, 2020, 14 pages. |
| Number | Date | Country | |
|---|---|---|---|
| 20170132199 A1 | May 2017 | US |
| Number | Date | Country | |
|---|---|---|---|
| 62252835 | Nov 2015 | US |
