Patent Grant
11838734
This relates generally to intelligent automated assistants and, more specifically, to the intelligent coordination of audio signal output adjustments among multiple electronic devices when, for example, an electronic device invokes an intelligent automated assistant.
Intelligent automated assistants (or digital assistants) can provide a beneficial interface between human users and electronic devices. Such assistants can allow users to interact with devices or systems using natural language in spoken and/or text forms. For example, a user can provide a speech input containing a user request to a digital assistant operating on an electronic device. The digital assistant can interpret the user's intent from the speech input 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 responsive to the user request can be returned to the user.
A location, such as a home or an office, may contain multiple electronic devices that are capable of outputting audio signals for digital assistant responses/interactions, music, video, timers, alarms, phone call alerts, text massage alerts, and/or the like. It can thus be desirable to coordinate the adjustment of audio signals being simultaneously output by multiple electronic devices (particularly, multiple electronic devices in a same room or area) when certain events corresponding to software applications and/or device modules are occurring at one or more of the multiple devices. In this manner, a user of an electronic device will be able to, for example, easily provide voice inputs (e.g., digital assistant requests) to the electronic device, as well as properly hear and respond to events occurring at the electronic device, despite the simultaneous output of audio signals from other, nearby electronic devices. This in turn may, for example, create an appearance of a single digital assistant that interacts with a user across the multiple electronic devices (e.g., when the user is providing a digital assistant request to an electronic device via voice input and/or receiving a digital assistant response). This may also improve the user's experience with an electronic device because, for example, the adjustment of audio signal outputs of nearby electronic devices will help prevent the user from not hearing or recognizing an event occurring at the electronic device and/or help prevent the user having to repeat digital assistant requests provided to the electronic device.
Example methods are disclosed herein. An example method includes, at a first electronic device: generating a local audio intent object associated with a software application stored on the first electronic device, wherein the local audio intent object includes one or more local audio parameters; after generating the local audio intent object, determining that a second electronic device is proximate to the first electronic device, wherein the second electronic device is outputting an audio signal; and in response to determining that the second electronic device is proximate to the first electronic device: generating a proximate audio intent object corresponding to the second electronic device based on the one or more local audio adjustment parameters and a round-trip time (RTT) of a communication connection between the first electronic device and the second electronic device; and transmitting the proximate audio intent object to the second electronic device via the communication connection, wherein the proximate audio intent object causes the second electronic device to adjust the output of the audio signal.
Example non-transitory computer-readable media are disclosed herein. An example non-transitory computer-readable storage medium stores one or more programs. The one or more programs comprise instructions, which when executed by one or more processors of a first electronic device, cause the first electronic device to: generate a local audio intent object associated with a software application stored on the first electronic device, wherein the local audio intent object includes one or more local audio parameters; after generating the local audio intent object, determine that a second electronic device is proximate to the first electronic device, wherein the second electronic device is outputting an audio signal; and in response to determining that the second electronic device is proximate to the first electronic device: generate a proximate audio intent object corresponding to the second electronic device based on the one or more local audio adjustment parameters and a round-trip time (RTT) of a communication connection between the first electronic device and the second electronic device; and transmit the proximate audio intent object to the second electronic device via the communication connection, wherein the proximate audio intent object causes the second electronic device to adjust the output of the audio signal.
Example electronic devices are disclosed herein. An example first electronic device comprises one or more processors; a memory; and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for generating a local audio intent object associated with a software application stored on the first electronic device, wherein the local audio intent object includes one or more local audio parameters; after generating the local audio intent object, determining that a second electronic device is proximate to the first electronic device, wherein the second electronic device is outputting an audio signal; and in response to determining that the second electronic device is proximate to the first electronic device: generating a proximate audio intent object corresponding to the second electronic device based on the one or more local audio adjustment parameters and a round-trip time (RTT) of a communication connection between the first electronic device and the second electronic device; and transmitting the proximate audio intent object to the second electronic device via the communication connection, wherein the proximate audio intent object causes the second electronic device to adjust the output of the audio signal.
Another example first electronic device comprises means for generating a local audio intent object associated with a software application stored on the first electronic device, wherein the local audio intent object includes one or more local audio parameters; means for after generating the local audio intent object, determining that a second electronic device is proximate to the first electronic device, wherein the second electronic device is outputting an audio signal; and means for in response to determining that the second electronic device is proximate to the first electronic device: generating a proximate audio intent object corresponding to the second electronic device based on the one or more local audio adjustment parameters and a round-trip time (RTT) of a communication connection between the first electronic device and the second electronic device; and transmitting the proximate audio intent object to the second electronic device via the communication connection, wherein the proximate audio intent object causes the second electronic device to adjust the output of the audio signal.
In some examples, generating a proximate audio intent object corresponding to the second electronic device based on the one or more local audio adjustment parameters and a round-trip time (RTT) of a communication connection between the first electronic device and the second electronic device, and transmitting the proximate audio intent object to the second electronic device via the communication connection, wherein the proximate audio intent object causes the second electronic device to adjust the output of the audio signal, may improve a user's experience with the first electronic device and/or the second electronic device. Specifically, generating a device-specific proximate audio intent object for adjusting the output of audio signals at the second electronic device helps ensure that the adjustment of those audio signals is in sync with software application/module events, user actions, and/or the current state of the first electronic device (as well as the first electronic device's adjustment of its own audio signal output (if any)). This in turn improves a user's experience with the first electronic device and/or the second electronic device because, for example, the adjustment of the audio signal output at the second electronic device will help prevent the user from not hearing or recognizing an event occurring at the first electronic device (e.g., an alarm going off at the first electronic device), and/or help prevent the user having to repeat digital assistant requests provided to the first electronic device, due to the second electronic device's simultaneous output of the audio signal.
In the following description of examples, reference is made to the accompanying drawings in which are shown by way of illustration specific examples that can be practiced. It is to be understood that other examples can be used and structural changes can be made without departing from the scope of the various examples.
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 input could be termed a second input, and, similarly, a second input could be termed a first input, without departing from the scope of the various described examples. The first input and the second input are both inputs and, in some cases, are separate and different inputs.
The terminology used in the description of the various described examples herein is for the purpose of describing particular examples only and is not intended to be limiting. As used in the description of the various described examples and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “includes,” “including,” “comprises,” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context. Similarly, the phrase “if it is determined” or “if [a stated condition or event] is detected” may be construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event],” depending on the context.
1. System and Environment
Specifically, a digital assistant is 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 seeks either an informational answer or performance of a task by the digital assistant. A satisfactory response to the user request includes a provision of the requested informational answer, a performance of the requested task, or a combination of the two. For example, a user asks the digital assistant a question, such as “Where am I right now?” Based on the user's current location, the digital assistant answers, “You are in Central Park near the west gate.” The user also requests 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 sometimes interacts 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 also provides 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 includes 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 facilitates the client-facing input and output processing for DA server 106. One or more processing modules 114 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 communicates with external services 120 through network(s) 110 for task completion or information acquisition. I/O interface to external services 118 facilitates such communications.
User device 104 can be any suitable electronic device. In some examples, user device 104 is a portable multifunctional device (e.g., device 200, described below with reference to
Examples of communication network(s) 110 include local area networks (LAN) and wide area networks (WAN), e.g., the Internet. Communication network(s) 110 is 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 is implemented on one or more standalone data processing apparatus or a distributed network of computers. In some examples, server system 108 also employs 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 communicates with DA server 106 via second user device 122. Second user device 122 is similar or identical to user device 104. For example, second user device 122 is similar to devices 200, 400, or 600 described below with reference to
In some examples, user device 104 is 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 is 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 includes one or more computer-readable storage mediums. The computer-readable storage mediums are, for example, tangible and non-transitory. Memory 202 includes high-speed random access memory and also includes 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 controls access to memory 202 by other components of device 200.
In some examples, a non-transitory computer-readable storage medium of memory 202 is used to store instructions (e.g., for performing aspects of processes 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 the processes described below) are stored on a non-transitory computer-readable storage medium (not shown) of the server system 108 or are divided between the non-transitory computer-readable storage medium of memory 202 and the non-transitory computer-readable storage medium of server system 108.
Peripherals interface 218 is 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 are implemented on a single chip, such as chip 204. In some other embodiments, they are 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 802.11 ac), 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 are 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 screen 212 and other input control devices 216, to peripherals interface 218. I/O subsystem 206 optionally includes display controller 256, optical sensor controller 258, intensity sensor controller 259, haptic feedback controller 261, and one or more input controllers 260 for other input or control devices. The one or more input controllers 260 receive/send electrical signals from/to other input control devices 216. The other input control devices 216 optionally include physical buttons (e.g., push buttons, rocker buttons, etc.), dials, slider switches, joysticks, click wheels, and so forth. In some alternate embodiments, input controller(s) 260 are, optionally, coupled to any (or none) of the following: a keyboard, an infrared port, a USB port, and a pointer device such as a mouse. The one or more buttons (e.g., 308,
A quick press of the push button disengages a lock of touch screen 212 or begin a process that uses gestures on the touch screen to unlock the device, as described in U.S. patent application Ser. No. 11/322,549, “Unlocking a Device by Performing Gestures on an Unlock Image,” filed Dec. 23, 2005, U.S. Pat. No. 7,657,849, which is hereby incorporated by reference in its entirety. A longer press of the push button (e.g., 306) turns power to device 200 on or off. The user is able to customize a functionality of one or more of the buttons. Touch screen 212 is used to implement virtual or soft buttons and one or more soft keyboards.
Touch-sensitive display 212 provides an input interface and an output interface between the device and a user. Display controller 256 receives and/or sends electrical signals from/to touch screen 212. Touch screen 212 displays visual output to the user. The visual output includes graphics, text, icons, video, and any combination thereof (collectively termed “graphics”). In some embodiments, some or all of the visual output correspond to user-interface objects.
Touch screen 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 screen 212 and display controller 256 (along with any associated modules and/or sets of instructions in memory 202) detect contact (and any movement or breaking of the contact) on touch screen 212 and convert the detected contact into interaction with user-interface objects (e.g., one or more soft keys, icons, web pages, or images) that are displayed on touch screen 212. In an exemplary embodiment, a point of contact between touch screen 212 and the user corresponds to a finger of the user.
Touch screen 212 uses LCD (liquid crystal display) technology, LPD (light emitting polymer display) technology, or LED (light emitting diode) technology, although other display technologies may be used in other embodiments. Touch screen 212 and display controller 256 detect contact and any movement or breaking thereof using any of a plurality of touch sensing technologies now known or later developed, including but not limited to capacitive, resistive, infrared, and surface acoustic wave technologies, as well as other proximity sensor arrays or other elements for determining one or more points of contact with touch screen 212. In an exemplary embodiment, projected mutual capacitance sensing technology is used, such as that found in the iPhone® and iPod Touch® from Apple Inc. of Cupertino, California.
A touch-sensitive display in some embodiments of touch screen 212 is analogous to the multi-touch sensitive touchpads described in the following U.S. Pat. No. 6,323,846 (Westerman et al.), U.S. Pat. No. 6,570,557 (Westerman et al.), and/or U.S. Pat. No. 6,677,932 (Westerman), and/or U.S. Patent Publication 2002/0015024A1, each of which is hereby incorporated by reference in its entirety. However, touch screen 212 displays visual output from device 200, whereas touch-sensitive touchpads do not provide visual output.
A touch-sensitive display in some embodiments of touch screen 212 is as described in the following applications: (1) U.S. patent application Ser. No. 11/381,313, “Multipoint Touch Surface Controller,” filed May 2, 2006; (2) U.S. patent application Ser. No. 10/840,862, “Multipoint Touchscreen,” filed May 6, 2004; (3) U.S. patent application Ser. No. 10/903,964, “Gestures For Touch Sensitive Input Devices,” filed Jul. 30, 2004; (4) U.S. patent application Ser. No. 11/048,264, “Gestures For Touch Sensitive Input Devices,” filed Jan. 31, 2005; (5) U.S. patent application Ser. No. 11/038,590, “Mode-Based Graphical User Interfaces For Touch Sensitive Input Devices,” filed Jan. 18, 2005; (6) U.S. patent application Ser. No. 11/228,758, “Virtual Input Device Placement On A Touch Screen User Interface,” filed Sep. 16, 2005; (7) U.S. patent application Ser. No. 11/228,700, “Operation Of A Computer With A Touch Screen Interface,” filed Sep. 16, 2005; (8) U.S. patent application Ser. No. 11/228,737, “Activating Virtual Keys Of A Touch-Screen Virtual Keyboard,” filed Sep. 16, 2005; and (9) U.S. patent application Ser. No. 11/367,749, “Multi-Functional Hand-Held Device,” filed Mar. 3, 2006. All of these applications are incorporated by reference herein in their entirety.
Touch screen 212 has, for example, a video resolution in excess of 100 dpi. In some embodiments, the touch screen has a video resolution of approximately 160 dpi. The user makes contact with touch screen 212 using any suitable object or appendage, such as a stylus, a finger, and so forth. In some embodiments, the user interface is designed to work primarily with finger-based contacts and gestures, which can be less precise than stylus-based input due to the larger area of contact of a finger on the touch screen. In some embodiments, the device translates the rough finger-based input into a precise pointer/cursor position or command for performing the actions desired by the user.
In some embodiments, in addition to the touch screen, device 200 includes 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 is a touch-sensitive surface that is separate from touch screen 212 or an extension of the touch-sensitive surface formed by the touch screen.
Device 200 also includes power system 262 for powering the various components. Power system 262 includes 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 also includes one or more optical sensors 264.
Device 200 optionally also includes one or more contact intensity sensors 265.
Device 200 also includes one or more proximity sensors 266.
Device 200 optionally also includes one or more tactile output generators 267.
Device 200 also includes 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 stores 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 screen 212 (in conjunction with display controller 256) and other touch-sensitive devices (e.g., a touchpad or physical click wheel). Contact/motion module 230 includes various software components for performing various operations related to detection of contact, such as determining if contact has occurred (e.g., detecting a finger-down event), determining an intensity of the contact (e.g., the force or pressure of the contact or a substitute for the force or pressure of the contact), determining if there is movement of the contact and tracking the movement across the touch-sensitive surface (e.g., detecting one or more finger-dragging events), and determining if the contact has ceased (e.g., detecting a finger-up event or a break in contact). Contact/motion module 230 receives contact data from the touch-sensitive surface. Determining movement of the point of contact, which is represented by a series of contact data, optionally includes determining speed (magnitude), velocity (magnitude and direction), and/or an acceleration (a change in magnitude and/or direction) of the point of contact. These operations are, optionally, applied to single contacts (e.g., one finger contacts) or to multiple simultaneous contacts (e.g., “multitouch”/multiple finger contacts). In some embodiments, contact/motion module 230 and display controller 256 detect contact on a touchpad.
In some embodiments, contact/motion module 230 uses a set of one or more intensity thresholds to determine whether an operation has been performed by a user (e.g., to determine whether a user has “clicked” on an icon). In some embodiments, at least a subset of the intensity thresholds are determined in accordance with software parameters (e.g., the intensity thresholds are not determined by the activation thresholds of particular physical actuators and can be adjusted without changing the physical hardware of device 200). For example, a mouse “click” threshold of a trackpad or touch screen display can be set to any of a large range of predefined threshold values without changing the trackpad or touch screen display hardware. Additionally, in some implementations, a user of the device is provided with software settings for adjusting one or more of the set of intensity thresholds (e.g., by adjusting individual intensity thresholds and/or by adjusting a plurality of intensity thresholds at once with a system-level click “intensity” parameter).
Contact/motion module 230 optionally detects a gesture input by a user. Different gestures on the touch-sensitive surface have different contact patterns (e.g., different motions, timings, and/or intensities of detected contacts). Thus, a gesture is, optionally, detected by detecting a particular contact pattern. For example, detecting a finger tap gesture includes detecting a finger-down event followed by detecting a finger-up (liftoff) event at the same position (or substantially the same position) as the finger-down event (e.g., at the position of an icon). As another example, detecting a finger swipe gesture on the touch-sensitive surface includes detecting a finger-down event followed by detecting one or more finger-dragging events, and subsequently followed by detecting a finger-up (liftoff) event.
Graphics module 232 includes various known software components for rendering and displaying graphics on touch screen 212 or other display, including components for changing the visual impact (e.g., brightness, transparency, saturation, contrast, or other visual property) of graphics that are displayed. As used herein, the term “graphics” includes any object that can be displayed to a user, including, without limitation, text, web pages, icons (such as user-interface objects including soft keys), digital images, videos, animations, and the like.
In some embodiments, graphics module 232 stores data representing graphics to be used. Each graphic is, optionally, assigned a corresponding code. Graphics module 232 receives, from applications etc., one or more codes specifying graphics to be displayed along with, if necessary, coordinate data and other graphic property data, and then generates screen image data to output to display controller 256.
Haptic feedback module 233 includes various software components for generating instructions used by tactile output generator(s) 267 to produce tactile outputs at one or more locations on device 200 in response to user interactions with device 200.
Text input module 234, which is, in some examples, a component of graphics module 232, provides soft keyboards for entering text in various applications (e.g., contacts 237, email 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 module 238 for use in location-based dialing; to camera module 243 as picture/video metadata; and to applications that provide location-based services such as weather widgets, local yellow page widgets, and map/navigation widgets).
Digital assistant client module 229 includes various client-side digital assistant instructions to provide the client-side functionalities of the digital assistant. For example, digital assistant client module 229 is 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 is also 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 is 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 communicates with DA server 106 using RF circuitry 208.
User data and models 231 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 include 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 utilizes 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 provides 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 also uses the contextual information to determine how to prepare and deliver outputs to the user. Contextual information is referred to as context data.
In some examples, the contextual information that accompanies the user input includes 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 is provided to DA server 106 as contextual information associated with a user input.
In some examples, the digital assistant client module 229 selectively provides 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 also elicits 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 passes 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 include the following modules (or sets of instructions), or a subset or superset thereof:
Examples of other applications 236 that are stored in memory 202 include other word processing applications, other image editing applications, drawing applications, presentation applications, JAVA-enabled applications, encryption, digital rights management, voice recognition, and voice replication.
In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, contacts module 237 are 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 screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, telephone module 238 are 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 uses any of a plurality of communications standards, protocols, and technologies.
In conjunction with RF circuitry 208, audio circuitry 210, speaker 211, microphone 213, touch screen 212, display controller 256, optical sensor 264, optical sensor controller 258, contact/motion module 230, graphics module 232, text input module 234, contacts module 237, and telephone module 238, video conference module 239 includes executable instructions to initiate, conduct, and terminate a video conference between a user and one or more other participants in accordance with user instructions.
In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, 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 screen 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 include graphics, photos, audio files, video files and/or other attachments as are supported in an MMS and/or an Enhanced Messaging Service (EMS). As used herein, “instant messaging” refers to both telephony-based messages (e.g., messages sent using SMS or MMS) and Internet-based messages (e.g., messages sent using XMPP, SIMPLE, or IMPS).
In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, GPS module 235, map module 254, and music player module, workout support module 242 includes executable instructions to create workouts (e.g., with time, distance, and/or calorie burning goals); communicate with workout sensors (sports devices); receive workout sensor data; calibrate sensors used to monitor a workout; select and play music for a workout; and display, store, and transmit workout data.
In conjunction with touch screen 212, display controller 256, optical sensor(s) 264, optical sensor controller 258, contact/motion module 230, graphics module 232, and image management module 244, camera module 243 includes executable instructions to capture still images or video (including a video stream) and store them into memory 202, modify characteristics of a still image or video, or delete a still image or video from memory 202.
In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, and camera module 243, image management module 244 includes executable instructions to arrange, modify (e.g., edit), or otherwise manipulate, label, delete, present (e.g., in a digital slide show or album), and store still and/or video images.
In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, browser module 247 includes executable instructions to browse the Internet in accordance with user instructions, including searching, linking to, receiving, and displaying web pages or portions thereof, as well as attachments and other files linked to web pages.
In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, 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 screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, and browser module 247, widget modules 249 are mini-applications that 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 screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, and browser module 247, the widget creator module 250 are used by a user to create widgets (e.g., turning a user-specified portion of a web page into a widget).
In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, search module 251 includes executable instructions to search for text, music, sound, image, video, and/or other files in memory 202 that match one or more search criteria (e.g., one or more user-specified search terms) in accordance with user instructions.
In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, audio circuitry 210, speaker 211, RF circuitry 208, and browser module 247, video and music player module 252 includes executable instructions that allow the user to download and play back recorded music and other sound files stored in one or more file formats, such as MP3 or AAC files, and executable instructions to display, present, or otherwise play back videos (e.g., on touch screen 212 or on an external, connected display via external port 224). In some embodiments, device 200 optionally includes the functionality of an MP3 player, such as an iPod (trademark of Apple Inc.).
In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, and text input module 234, notes module 253 includes executable instructions to create and manage notes, to-do lists, and the like in accordance with user instructions.
In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact/motion module 230, graphics module 232, text input module 234, GPS module 235, and browser module 247, map module 254 are used to receive, display, modify, and store maps and data associated with maps (e.g., driving directions, data on stores and other points of interest at or near a particular location, and other location-based data) in accordance with user instructions.
In conjunction with touch screen 212, display controller 256, contact/motion module 230, graphics module 232, audio circuitry 210, speaker 211, RF circuitry 208, text input module 234, 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 can be combined or otherwise rearranged in various embodiments. For example, video player module 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 is 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 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 is called the hit view, and the set of events that are recognized as proper inputs is 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 utilizes or calls 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 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 also includes 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 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 also includes one or more physical buttons, such as “home” or menu button 304. As described previously, menu button 304 is used to navigate to any application 236 in a set of applications that is executed on device 200. Alternatively, in some embodiments, the menu button is implemented as a soft key in a GUI displayed on touch screen 212.
In one embodiment, device 200 includes touch screen 212, menu button 304, push button 306 for powering the device on/off and locking the device, volume adjustment button(s) 308, subscriber identity module (SIM) card slot 310, headset jack 312, and docking/charging external port 224. Push button 306 is, optionally, used to turn the power on/off on the device by depressing the button and holding the button in the depressed state for a predefined time interval; to lock the device by depressing the button and releasing the button before the predefined time interval has elapsed; and/or to unlock the device or initiate an unlock process. In an alternative embodiment, device 200 also accepts verbal input for activation or deactivation of some functions through microphone 213. Device 200 also, optionally, includes one or more contact intensity sensors 265 for detecting intensity of contacts on touch screen 212 and/or one or more tactile output generators 267 for generating tactile outputs for a user of device 200.
Each of the above-identified elements in
Attention is now directed towards embodiments of user interfaces that 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 are 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, are 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 permit device 600 to be worn by a user.
Input mechanism 608 is a microphone, in some examples. Personal electronic device 600 includes, for example, 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 are operatively connected to I/O section 614.
Memory 618 of personal electronic device 600 is a non-transitory computer-readable storage medium, for storing computer-executable instructions, which, when executed by one or more computer processors 616, for example, cause the computer processors to perform the techniques and processes described below. The computer-executable instructions, for example, are also stored and/or transported within any non-transitory computer-readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. Personal electronic device 600 is not limited to the components and configuration of
As used here, the term “affordance” refers to a user-interactive graphical user interface object that is, for example, 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 includes 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 receives 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 is 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 is 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 is 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 includes 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 includes 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 couples 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, receives 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 includes 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 includes wired communication port(s) 712 and/or wireless transmission and reception circuitry 714. The wired communication port(s) receives and send communication signals via one or more wired interfaces, e.g., Ethernet, Universal Serial Bus (USB), FIREWIRE, etc. The wireless circuitry 714 receives and sends RF signals and/or optical signals from/to communications networks and other communications devices. The wireless communications 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 enables 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, stores 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, stores instructions for performing the processes described below. One or more processors 704 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) 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 communications between various hardware, firmware, and software components.
Communications module 720 facilitates communications between digital assistant system 700 with other devices over network communications interface 708. For example, communications module 720 communicates with RF circuitry 208 of electronic devices such as devices 200, 400, and 600 shown in
User interface module 722 receives 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 also prepares and delivers 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 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 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 include resource management applications, diagnostic applications, or scheduling applications, for example.
Memory 702 also stores digital assistant module 726 (or the server portion of a digital assistant). In some examples, digital assistant module 726 includes 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 processing module 740. Each of these modules has 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 758.
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 includes one or more ASR systems 758. The one or more ASR systems 758 can process the speech input that is received through I/O processing module 728 to produce a recognition result. Each ASR system 758 includes a front-end speech pre-processor. The front-end speech pre-processor extracts representative features from the speech input. For example, the front-end speech pre-processor performs 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 758 includes one or more speech recognition models (e.g., acoustic models and/or language models) and implements one or more speech recognition engines. Examples of speech recognition models include Hidden Markov Models, Gaussian-Mixture Models, Deep Neural Network Models, n-gram language models, and other statistical models. Examples of speech recognition engines 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 are 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 is 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 is passed to natural language processing module 732 for intent deduction. In some examples, STT processing module 730 produces multiple candidate text representations of the speech input. Each candidate text representation is a sequence of words or tokens corresponding to the speech input. In some examples, each candidate text representation is associated with a speech recognition confidence score. Based on the speech recognition confidence scores, STT processing module 730 ranks the candidate text representations and provides the n-best (e.g., n highest ranked) candidate text representation(s) to natural language processing module 732 for intent deduction, where n is a predetermined integer greater than zero. For example, in one example, only the highest ranked (n=1) candidate text representation is passed to natural language processing module 732 for intent deduction. In another example, the five highest ranked (n=5) candidate text representations are 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 includes and/or accesses a vocabulary of recognizable words via phonetic alphabet conversion module 731. Each vocabulary word is associated with one or more candidate pronunciations of the word represented in a speech recognition phonetic alphabet. In particular, the vocabulary of recognizable words includes a word that is associated with a plurality of candidate pronunciations. For example, the vocabulary includes the word “tomato” that is associated with the candidate pronunciations of and
. Further, vocabulary words are associated with custom candidate pronunciations that are based on previous speech inputs from the user. Such custom candidate pronunciations are stored in STT processing module 730 and are associated with a particular user via the user's profile on the device. In some examples, the candidate pronunciations for words are determined based on the spelling of the word and one or more linguistic and/or phonetic rules. In some examples, the candidate pronunciations are manually generated, e.g., based on known canonical pronunciations.
In some examples, the candidate pronunciations are ranked based on the commonness of the candidate pronunciation. For example, the candidate pronunciation is 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 are ranked based on whether the candidate pronunciation is a custom candidate pronunciation associated with the user. For example, custom candidate pronunciations are 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 are associated with one or more speech characteristics, such as geographic origin, nationality, or ethnicity. For example, the candidate pronunciation
is associated with the United States, whereas the candidate pronunciation
is associated with Great Britain. Further, the rank of the candidate pronunciation is 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) is ranked higher than the candidate pronunciation
(associated with Great Britain). In some examples, one of the ranked candidate pronunciations is selected as a predicted pronunciation (e.g., the most likely pronunciation).
When a speech input is received, STT processing module 730 is 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 first identifies 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 uses approximate matching techniques to determine words in an utterance. Thus, for example, the STT processing module 730 determines 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.
Natural language processing module 732 (“natural language processor”) of the digital assistant takes the n-best candidate text representation(s) (“word sequence(s)” or “token sequence(s)”) generated by STT processing module 730, and attempts to associate each of the candidate text representations with one or more “actionable intents” recognized by the digital assistant. An “actionable intent” (or “user intent”) represents 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 is 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 is 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, also dependents 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 also receives contextual information associated with the user request, e.g., from I/O processing module 728. The natural language processing module 732 optionally uses the contextual information to clarify, supplement, and/or further define the information contained in the candidate text representations received from STT processing module 730. The contextual information includes, 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 is, in some examples, dynamic, and changes with time, location, content of the dialogue, and other factors.
In some examples, the natural language processing is based on, e.g., ontology 760. Ontology 760 is 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” represents a task that the digital assistant is capable of performing, i.e., it is “actionable” or can be acted on. A “property” represents 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 defines how a parameter represented by the property node pertains to the task represented by the actionable intent node.
In some examples, ontology 760 is made up of actionable intent nodes and property nodes. Within ontology 760, each actionable intent node is linked to one or more property nodes either directly or through one or more intermediate property nodes. Similarly, each property node is 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” are sub-nodes of the property node “restaurant,” and are each 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 property nodes, is described as a “domain.” In the present discussion, each domain is 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 includes all the domains (and hence actionable intents) that the digital assistant is capable of understanding and acting upon. In some examples, ontology 760 is 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 are clustered under a “super domain” in ontology 760. For example, a “travel” super-domain includes a cluster of property nodes and actionable intent nodes related to travel. The actionable intent nodes related to travel includes “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) 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” 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 is 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 are the so-called “vocabulary” associated with the node. The respective set of words and/or phrases associated with each node are 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 receives the candidate text representations (e.g., text string(s) or token sequence(s)) from STT processing module 730, and for each candidate representation, determines what nodes are implicated by the words in the candidate text representation. In some examples, if a word or phrase in the candidate text representation is found to be associated with one or more nodes in ontology 760 (via vocabulary index 744), the word or phrase “triggers” or “activates” those nodes. Based on the quantity and/or relative importance of the activated nodes, natural language processing module 732 selects 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 is selected. In some examples, the domain having the highest confidence value (e.g., based on the relative importance of its various triggered nodes) is selected. In some examples, the domain is 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 includes 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 uses 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 is 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.
It should be recognized that in some examples, natural language processing module 732 is implemented using one or more machine learning mechanisms (e.g., neural networks). In particular, the one or more machine learning mechanisms are configured to receive a candidate text representation and contextual information associated with the candidate text representation. Based on the candidate text representation and the associated contextual information, the one or more machine learning mechanisms are configured to determine intent confidence scores over a set of candidate actionable intents. Natural language processing module 732 can select one or more candidate actionable intents from the set of candidate actionable intents based on the determined intent confidence scores. In some examples, an ontology (e.g., ontology 760) is also used to select the one or more candidate actionable intents from the set of candidate actionable intents.
Other details of searching an ontology based on a token string are 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 generates a structured query to represent the identified actionable intent. In some examples, the structured query includes 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 says “Make me a dinner reservation at a sushi place at 7.” In this case, natural language processing module 732 is 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 includes 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 generates 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} are not specified in the structured query based on the information currently available. In some examples, natural language processing module 732 populates 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 populates a {location} parameter in the structured query with GPS coordinates from the user device.
In some examples, natural language processing module 732 identifies multiple candidate actionable intents for each candidate text representation received from STT processing module 730. Further, in some examples, a respective structured query (partial or complete) is generated for each identified candidate actionable intent. Natural language processing module 732 determines an intent confidence score for each candidate actionable intent and ranks the candidate actionable intents based on the intent confidence scores. In some examples, natural language processing module 732 passes the generated structured query (or queries), including any completed parameters, to task flow processing module 736 (“task flow processor”). In some examples, the structured query (or queries) for the m-best (e.g., m highest ranked) candidate actionable intents are provided to task flow processing module 736, where m is a predetermined integer greater than zero. In some examples, the structured query (or queries) for the m-best candidate actionable intents are provided to task flow processing module 736 with the corresponding candidate text representation(s).
Other details of inferring a user intent based on multiple candidate actionable intents determined from multiple candidate text representations of a speech input are described in U.S. Utility application Ser. No. 14/298,725 for “System and Method for Inferring User Intent From Speech Inputs,” filed Jun. 6, 2014, the entire disclosure of which is incorporated herein by reference.
Task flow processing module 736 is configured to receive the structured query (or queries) 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 are provided in task flow models 754. In some examples, task flow models 754 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 needs 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 invokes dialogue flow processing module 734 to engage in a dialogue with the user. In some examples, dialogue flow processing module 734 determines how (and/or when) to ask the user for the additional information and receives and processes the user responses. The questions are provided to and answers are received from the users through I/O processing module 728. In some examples, dialogue flow processing module 734 presents 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 generates 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 then populates 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 proceeds to perform the ultimate task associated with the actionable intent. Accordingly, task flow processing module 736 executes 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” includes steps and instructions for contacting a restaurant and actually requesting a reservation for a particular party size at a particular time. For example, using a structured query such as: {restaurant reservation, restaurant=ABC Café, date=3/12/2012, time=7 pm, party size=5}, task flow processing module 736 performs 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 employs 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 acts 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 are specified by a respective service model among service models 756. Service processing module 738 accesses the appropriate service model for a service and generates 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 submits 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 establishes a network connection with the online reservation service using the web address stored in the service model, and sends 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 are 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 is a dialogue response to the speech input that at least partially fulfills the user's intent. Further, in some examples, the generated response is output as a speech output. In these examples, the generated response is sent to speech synthesis processing 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 is data content relevant to satisfying a user request in the speech input.
In examples where task flow processing module 736 receives multiple structured queries from natural language processing module 732, task flow processing module 736 initially processes the first structured query of the received structured queries to attempt to complete the first structured query and/or execute one or more tasks or actions represented by the first structured query. In some examples, the first structured query corresponds to the highest ranked actionable intent. In other examples, the first structured query is selected from the received structured queries based on a combination of the corresponding speech recognition confidence scores and the corresponding intent confidence scores. In some examples, if task flow processing module 736 encounters an error during processing of the first structured query (e.g., due to an inability to determine a necessary parameter), the task flow processing module 736 can proceed to select and process a second structured query of the received structured queries that corresponds to a lower ranked actionable intent. The second structured query is selected, for example, based on the speech recognition confidence score of the corresponding candidate text representation, the intent confidence score of the corresponding candidate actionable intent, a missing necessary parameter in the first structured query, or any combination thereof.
Speech synthesis processing module 740 is configured to synthesize speech outputs for presentation to the user. Speech synthesis processing module 740 synthesizes speech outputs based on text provided by the digital assistant. For example, the generated dialogue response is in the form of a text string. Speech synthesis processing module 740 converts the text string to an audible speech output. Speech synthesis processing module 740 uses 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 processing module 740 is configured to synthesize individual words based on phonemic strings corresponding to the words. For example, a phonemic string is associated with a word in the generated dialogue response. The phonemic string is stored in metadata associated with the word. Speech synthesis processing module 740 is 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 processing module 740, speech synthesis is performed on a remote device (e.g., the server system 108), and the synthesized speech is 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 is possible to obtain higher quality speech outputs than would be practical with client-side synthesis.
Additional details on digital assistants can be found in the U.S. Utility application Ser. No. 12/987,982, entitled “Intelligent Automated Assistant,” filed Jan. 10, 2011, and U.S. Utility application Ser. No. 13/251,088, entitled “Generating and Processing Task Items That Represent Tasks to Perform,” filed Sep. 30, 2011, the entire disclosures of which are incorporated herein by reference.
4. Systems and Techniques for Coordinating the Adjustment of Audio Signal Outputs Across Multiple Electronic Devices
System 800 is implemented using hardware, software, or a combination of hardware and software to carry out the functions discussed herein. Further, system 800 is exemplary, and thus system 800 can have more or fewer components than shown, can combine two or more components, or can have a different configuration or arrangement of the components. Although the below discussion describes functions being performed at a single module of system 800, it is to be understood that such functions can be performed at other modules of system 800 and that such functions can be performed at more than one module of system 800.
To illustrate the examples discussed herein, system 800 and
As shown in
Local applications 802 are stored on an electronic device implementing system 800 (referred to below as the “local electronic device”). For example, local applications 802 are stored on user device 902 and user device 1002 of
When an event corresponding to a local application 802 is occurring (or, in some examples, is about to occur, e.g., within 1 second, 2 seconds, 5 seconds, 30 seconds, or the like) at the local electronic device and that event is associated with the adjustment of audio signal outputs (e.g., stopping audio signal outputs, lowering a volume level of audio signal outputs, filtering audio signal outputs, and/or the like), the local application 802 generates a local audio intent object. A local audio intent object includes an object (e.g., data structure, programming object, or the like) that corresponds to the intent and/or desire of a local application 802 to adjust the output of an audio signal at the local electronic device and/or any proximate (e.g., nearby) electronic devices. In some examples, events that are associated with the adjustment of audio signal outputs are predetermined (e.g., predetermined based on the local application 802).
For example, as shown in
Each local audio intent object that a local application 802 generates includes at least one of a local audio adjustment start time (e.g., data indicating a time at which audio adjustment will begin), a local audio adjustment duration (e.g., data indicating an amount of time that the output of an audio signal will be adjusted), and one or more application-specific adjustment parameters (e.g., data indicating a type of audio adjustment requested by the local application 802). There are various types of audio signal output adjustments that a local application 802 may request (e.g., and which may be indicated by application-specific adjustment parameters included in a local audio intent object). In some examples, the audio signal output adjustment includes stopping the output of an audio signal. In other examples, the audio signal output adjustment includes lowering a volume level of the output of an audio signal. In some examples, the audio signal output adjustment includes filtering the audio signal with low pass, band pass, and/or high pass filters. In some examples, the audio signal output adjustment includes lowering a volume level of the output of an audio signal and filtering the audio signal with low pass, band pass, and/or high pass filters.
In some examples, a local audio intent object includes all three of the audio adjustment parameters described above. For example, in response to user 906 providing voice input 904, the local audio intent object generated by the digital assistant software application/module of user device 902 (e.g., digital assistant application 802A) may include (1) a local audio adjustment start time of 1.7 seconds (indicating that the audio signal output adjustment should begin in 1.7 seconds), (2) a local audio adjustment duration of 1 minute (indicating that the audio signal output adjustment should last for 1 minute), and (3) an application-specific adjustment parameter indicating that the audio signal output adjustment should include lowering a volume level of the output of the audio signal (e.g., to a predetermined volume level).
In some examples, a local audio intent object does not include all three of the parameters described above (and instead only includes one or two of the parameters). For example, if in the example illustrated in
As shown in
After a local application 802 generates a local audio intent object, the local application 802 provides the local audio intent object to local intentions module 806. For example, the digital assistant software application/module of user device 902 (e.g., digital assistant application 802A) will provide a local audio intent object to local intentions module 806 after detecting the digital assistant trigger in voice input 904. Local intentions module 806 is configured to receive and store local audio intent objects from one or more local applications 802. Local intentions module 806 stores local audio intent objects based on the audio adjustment duration included in a local audio intent object. In some examples, if a local audio intent object includes an audio adjustment duration (with or without an audio adjustment start time), local intentions module 806 will store the local audio intent object until the audio adjustment duration has elapsed. In other examples, if a local audio intent object does not include an audio adjustment duration (with or without an audio adjustment start time), local intentions module 806 will store the local audio intent object until the software application/module that generated the local audio intent object instructs local intentions module 806 to withdraw or remove the local audio intent object. In yet other examples, if a local audio intent object does not include an audio adjustment duration (with or without an audio adjustment start time), local intentions module 806 will associate the local audio intent object with a predetermined audio adjustment duration (e.g., 5 seconds, 30 seconds, 1 minute, or the like) and store the local audio intent object until the predetermined audio adjustment duration has elapsed.
As shown in
Proximate intentions module 808 is configured to receive a local audio intent object from local intentions module 806. As will be described in greater detail below, in examples where local intentions module 806 provides two or more local audio intent objects to baseline intention module 812, proximate intentions module 808 is configured to receive a baseline audio adjustment intention (e.g., data corresponding to one or more baseline audio adjustment parameters) from baseline intention module 812.
Proximate intentions module 808 is further configured to determine whether there are any proximate electronic devices (e.g., nearby electronic devices relative to the physical location of the local electronic device). In some examples, proximate intentions module 808 determines whether there are any proximate electronic devices in response to receiving a local audio intent object from local intentions module 806 (or, in some examples, a baseline audio adjustment intention from baseline intention module 812). In some examples, proximate intentions module 808 periodically determines whether there are any proximate electronic devices (e.g., every 5 seconds, 30 seconds, 1 minute, or the like).
In some examples, electronic devices that are proximate to the local electronic device are predetermined (e.g., based on data and/or information included in a software application stored on the local electronic device (e.g., HomeKit), a website, and/or the like). In some examples, proximate intentions module 808 determines whether there are any proximate electronic devices based on predefined data indicating a location of an electronic device (e.g., predefined data and/or information included in a software application stored on the local electronic device (e.g., HomeKit), a website, and/or the like) and a current location of the local electronic device. For example, returning to
In some examples, proximate intentions module 808 determines whether there are any proximate electronic devices based on proximity information corresponding to one or more electronic devices. In some examples, proximate intentions module 808 determines the proximity information corresponding to an electronic device based on one or more signals received from the electronic device via network(s) 809. For example, network(s) 809 may be a near-field communication connection, a short-range communication connection (e.g., ultra-wideband (UWB), Bluetooth, and/or BTLE), and/or a Wi-Fi connection. For example, returning to
After determining that there are one or more proximate electronic devices 810, proximate intentions module 808 generates a device-specific proximate audio intent object and determines a device-specific keep-alive time for each of the one or more proximate electronic devices 810. A proximate audio intent object includes an object (e.g., data structure, programming object, or the like) that corresponds to the intent and/or desire to adjust the output of an audio signal at a specific proximate electronic device. A proximate audio intent object includes at least one of a proximate audio adjustment start time (e.g., data indicating a time at which audio adjustment will begin), a proximate audio adjustment duration (e.g., data indicating an amount of time that the output of an audio signal will be adjusted), and one or more application-specific adjustment parameters (e.g., data indicating a type of audio adjustment requested by the local application 802). As will be explained in greater detail below, a keep-alive time is a period of time after the local electronic device transmits a proximate audio intent object to a proximate electronic device 810 that the local electronic waits before sending another (e.g., new/follow-up) proximate audio intent object to the proximate electronic device 810.
Proximate intentions module 808 generates a proximate audio intent object, and determines a keep-alive time, for a proximate electronic device 810 based on the local audio adjustment parameters included in the received local audio intent object. For example, a proximate audio adjustment start time of a proximate audio intent object will be the same as a local audio adjustment start time (e.g., so that the local electronic device and the proximate electronic device 810 concurrently adjust the output of audio signals). Further, the application-specific adjustment parameters included in the proximate audio intent object will be the same as the application-specific adjustment parameters included in the local audio intent object (e.g., so that the local electronic device and the proximate electronic device 810 adjust the output of audio signals in a similar manner). However, the proximate audio adjustment duration will be shorter/less than the local audio adjustment duration. For example, returning to
In some examples, proximate intentions module 808 generates a proximate audio intent object, and determines a keep-alive time, for a proximate electronic device 810 further based on a round-trip time (RTT) of a communication connection (e.g., a near-field communication connection, a short-range communication connection (e.g., ultra-wideband (UWB), Bluetooth, and/or BTLE), and/or a Wi-Fi connection) between the local electronic device and the proximate electronic device 810. For example, returning to
Proximate intentions module 808 is further configured to transmit generated proximate audio intent objects to proximate electronic devices 810 via network(s) 809. Upon receiving their respective proximate audio intent objects, each of the proximate electronic devices 810 that is outputting an audio signal will adjust the output of the audio signal based on the proximate audio adjustment parameters included in the received proximate audio intent object. A proximate electronic device 810 will continue adjusting the output of its respective audio signal for the entirety of the proximate audio adjustment duration or until the proximate electronic device receives a request or instruction from the local electronic device (e.g., from proximate intentions module 808) for the proximate electronic device to cease the adjustment of its audio signal output. For example, as shown in
Once proximate intentions module 808 transmits a proximate audio intent object to a proximate electronic device 810, the keep-alive time corresponding to the proximate electronic device 810 begins to run. After the keep-alive time elapses (e.g., immediately after or soon after), proximate intentions module 808 generates a new proximate audio intent object, and determines a new keep-alive time, for the proximate electronic device 810.
A keep-alive time for a proximate electronic device 810 is shorter/less than a corresponding proximate audio adjustment duration for the proximate electronic device 810. For example, if the proximate audio adjustment duration included in the proximate audio intent object that user device 902 transmits to smart speaker 908 is 8 seconds, then the keep-alive time for smart speaker 908 may be 4 seconds. In this manner, the reduced keep-alive time helps ensure that a proximate electronic device 810 (e.g., smart speaker 908) does not stop adjusting the output of an audio signal (e.g., music audio signals 910) when it is not supposed to (due to, for example, a delay in the transmission of a new/follow-up proximate audio intent object). For instance, returning to the previous example, a 4-second keep-alive time and an 8-second proximate audio adjustment duration provides a 4-second buffer for a new/follow-up proximate audio adjustment intent object (sent to smart speaker 908 after the 4-second keep-alive time has elapsed) to reach smart speaker 908 and continue the adjustment of volume level 912 (e.g., for another 8 seconds) once the proximate audio adjustment duration of the previous/preceding proximate audio intent objet has elapsed.
Generating a new proximate audio intent object includes proximate intentions module 808 determining updated values for the proximate audio adjustment parameters (to be included in the new proximate audio intent object) based on the local audio adjustment parameters of the local audio intent object, and/or the RTT of the communication connection between the local electronic device and the proximate electronic device 810, and/or the current state of the proximate electronic device 810. Similarly, determining a new keep-alive time includes proximate intentions module 808 determining an updated value for the keep-alive time based on the local audio adjustment parameters of the local audio intent object, and/or the RTT of the communication connection between the local electronic device and the proximate electronic device 810, and/or the current state of the proximate electronic device 810.
For example, returning to
In some examples, the updated proximate audio adjustment parameters included in the new proximate audio intent object are identical to the previous/preceding proximate audio intent object (e.g., identical audio adjustment durations). In some examples, the new keep-alive time is identical to the previous/preceding keep-alive time.
Proximate intentions module 808 will continue to periodically (1) generate a new proximate audio intent object, (2) determine a new keep-alive time, and (3) transmit the new proximate audio intent object to a proximate electronic device 810 when a previous/preceding keep-alive time elapses until the local audio adjustment time elapses. For example, returning to
After a proximate audio adjustment duration elapses (e.g., immediately after or soon after) and a proximate electronic device 810 has not received a new proximate audio intent object from the local electronic device (e.g., such that the proximate electronic device 810 is not currently storing a proximate audio intent object), the proximate electronic device 810 will adjust the output of an audio signal back to the initial output characteristics. Returning to the previous example, after the 4-second proximate audio adjustment duration of the final proximate audio intent object received by smart speaker 908 elapses, smart speaker 908 may raise the volume level 912 of the output of music audio signals 910 back to its initial level/value.
As described above, and as shown in
As mentioned above, when local intentions module 806 receives a local audio intent object from a local application 802 and local intentions module 806 is not storing any additional local audio intent objects, local intentions module 806 provides the received local audio intent object directly to local audio adjustment module 814 (e.g., immediately before, immediately after, or at the same time local intentions module 806 provides the intent object/local audio adjustment parameters directly to proximate intentions module 808). For example, returning to
After receiving the local audio intent object, local audio adjustment module 814 determines whether the local electronic device is currently outputting an audio signal (e.g., based on data/information provided to local audio adjustment module 814 by local audio system 816). In some examples, local audio adjustment module 814 periodically determines whether the local electronic device is outputting an audio signal (e.g., every 0.5 seconds, every 2 seconds, every 5 seconds, or the like).
In some examples, a local electronic device (e.g., user device 902) is outputting an audio signal (e.g., music audio signals, audio signals for a video, and/or the like) when a local application 802 generates a local audio intent object. Thus, if local audio adjustment module 814 determines that the local electronic device is currently outputting an audio signal, local audio adjustment module 814 will provide a request or instruction to local audio system 816 for local audio system 816 to adjust the output of the audio signal in accordance with the local audio adjustment parameters included in the local audio intent object. In some of these examples, local audio system 816 adjusts the output of an audio signal at the same time that one or more proximate electronic device 810 adjust their respective output of audio signals. For example, returning to
Alternatively, if local audio adjustment module 814 determines that the local electronic device is not currently outputting an audio signal (e.g., as illustrated in
As mentioned above, in some examples, local intentions module 806 receives two or more local audio intent objects from local applications 802 (e.g., from the same local application 802 or from multiple local applications 802). For example, local intentions module 806 may receive two or more local audio intent objects at the same time (e.g., from different software applications/modules). As another example, local intentions module 806 may receive a local audio intent object from a local application 802 while a previously-received/stored local audio intent object is still active (or, in other words, when a previously-received/stored local audio intent object has not yet been withdrawn/removed from local intentions module 806 (e.g., because the local audio adjustment duration of that previously-received/stored local audio intent object has not yet elapsed)). In these examples, local intentions module 806 provides all of the local audio intent objects that it is currently storing to baseline intention module 812.
Baseline intention module 812 is configured to determine a baseline audio adjustment intention, which is an overall local audio adjustment intention representing a combination of all current/active local audio intent objects (and their respective local audio adjustment parameters). Specifically, a baseline audio adjustment intention includes a baseline audio adjustment start time (e.g., data indicating a time at which audio adjustment will begin), which corresponds to the earliest local audio adjustment start time included in all of the local audio intent objects received from local intentions module 806 (and currently being stored by local intentions module 806). A baseline audio adjustment intention further includes a baseline audio adjustment duration (e.g., data indicating an amount of time that the output of an audio signal will be adjusted), which corresponds to the longest local audio adjustment duration included in all of the local audio intent objects received from local intentions module 806 (and currently being stored by local intentions module 806). Determining the baseline audio adjustment start time and the baseline audio adjustment duration based on the earliest local audio adjustment start time and the longest/greatest local audio adjustment duration, respectively, ensures that a local electronic device and/or proximate electronic devices 810 will continually adjust the output of audio signals to cover the requested adjustment of all active local audio intent objects instead of, for example, separately adjusting and readjusting the output of audio signals for each individual local audio intent object. This in turn improves a user's experience with the local electronic device and/or proximate electronic devices because, for example, repeatedly adjusting and readjusting audio signals in succession can be distracting and/or annoying to a user.
A baseline audio adjustment intention further includes one or more application-specific adjustment parameters (e.g., data indicating a type of audio adjustment requested by one or more local applications 802). In some examples, the one or more application-specific adjustment parameters included in the baseline audio adjustment intention correspond to all of the application-specific adjustment parameters included in all of the local audio intent objects received from local intentions module 806 (and currently being stored by local intentions module 806). In other examples, the baseline audio adjustment intention only includes a predetermined number of the most common application-specific adjustment parameters included in all of the local audio intent objects received from local intentions module 806 (and currently being stored by local intentions module 806). For example, the baseline audio adjustment intention may only include the most common type of audio adjustment included in all of the local audio intent objects.
Note, in some examples, even when local intentions module 806 is only storing a single local audio intent object, local intentions module 806 provides the local audio intent object to baseline intentions module 812 (instead of providing the local audio intent directly to proximate intentions module 808 and local audio adjustment module 814). In these examples, the baseline audio adjustment parameters for the baseline audio adjustment intention (e.g., the baseline audio adjustment start time, the baselines audio adjustment duration, and the one or more application-specific parameters) will be the same as the local audio adjustment parameters included in the local audio intent object.
As shown in
Specifically, after receiving a baseline audio adjustment intention (e.g., immediately after or soon after), proximate intentions module 808 determines whether there are any proximate electronic devices (e.g., nearby electronic devices relative to the physical location of the local electronic device). After determining that there are one or more proximate electronic devices 810, proximate intentions module 808 generates a device-specific proximate audio intent object and determines a device-specific keep-alive time for each of the one or more proximate electronic devices 810 (based on baseline audio adjustment parameters instead of on local audio adjustment parameters). For example, a proximate audio adjustment start time of a proximate audio intent object will be the same as a baseline audio adjustment start time. The application-specific adjustment parameters included in the proximate audio intent object will be the same as the application-specific adjustment parameters included in the baseline audio intention. Further, the proximate audio adjustment duration will be shorter/less than the baseline audio adjustment duration. For example, if a baseline audio adjustment intention includes a baseline audio adjustment duration of 1 minute, proximate intentions module 808 may determine a proximate audio adjustment duration of 8 seconds. In some examples, proximate intentions module 808 further considers RTT data/information and/or proximate electronic device current state data/information (e.g., as described above) when generating proximate audio intent objects based on a baseline audio intention.
After generating device-specific proximate audio intent objects, proximate intentions module 808 provides the proximate audio intent objects to proximate electronic devices 810 via network(s) 809. Proximate intentions module will then periodically generate and transmit follow-up/new proximate audio intent objects as described above, but determined based at least on the baseline audio adjustment parameters.
After receiving a baseline audio adjustment intention, local audio adjustment module 814 determines whether the local electronic device is currently outputting an audio signal (e.g., based on data/information provided to local audio adjustment module 814 by local audio system 816). In some examples, a local electronic device (e.g., user device 902) is outputting an audio signal (e.g., music audio signals, audio signals for a video, and/or the like) when baseline intention module 812 determines a baseline audio adjustment intention. Thus, if local audio adjustment module 814 determines that the local electronic device is currently outputting an audio signal, local audio adjustment module 814 will provide a request or instruction to local audio system 816 for local audio system 816 to adjust the output of the audio signal in accordance with the baseline audio adjustment parameters included in the baseline audio adjustment intention. In some of these examples, local audio system 816 adjusts the output of an audio signal at the same time that one or more proximate electronic device 810 adjust their respective output of audio signals. In other examples, local audio system 816 adjusts the output of an audio signal being output by a local electronic device before or after (e.g., immediately before or after) one or more proximate electronic devices 810 adjust their respective outputs of audio signals. Alternatively, if local audio adjustment module 814 determines that the local electronic device is not currently outputting an audio signal (e.g., as illustrated in
Baseline intention module 812 is further configured to determine a new/updated baseline audio adjustment intention when there is a current/active baseline audio intention and/or a current/active local audio intent object, and (1) one or more new local audio intent objects are received from local intentions module 806 or (2) a local audio intent object becomes inactive (e.g., due to a local audio adjustment duration of a local audio intent object elapsing and/or due to a local audio intent object being removed or withdrawn from local intentions module 806). In other words, baseline intention module 812 is configured to determine a new/updated baseline audio adjustment intention even when proximate intentions module 808 is currently transmitting proximate audio intent objects to one or more proximate electronic devices 810 and/or when local audio adjustment module 814 is currently adjusting (via local audio system 816) the local electronic device's output of an audio signal (e.g., currently transmitting proximate audio intent objects/adjusting the local electronic device's audio signal output based on a current/active local audio intent object or a current/active baseline audio adjustment intention).
After baseline intention module 812 determines a new/updated baseline audio adjustment intention, baseline intention module 812 provides the new/updated baseline audio adjustment intention to proximate intentions module 808 so that proximate intentions module 808 may subsequently generate proximate audio intent objects based on the new/updated baseline audio adjustment intention (e.g., which includes determining new keep-alive times and proximate audio adjustment durations as described above) for one or more proximate electronic devices to which proximate intentions module is currently transmitting proximate audio intent objects. Baseline intention module 812 further provides the new/updated baseline audio adjustment intentions to local audio adjustment module 814 so that local audio adjustment module 814 may instruct or request local audio system 816 to adjust the local electronic device's output of audio signals based on the new/updated baseline audio adjustment intention instead of a current/active baseline audio intention or a current/active local audio intent object. In this manner, baseline intention module 812 ensures that the current/active adjustment of audio signal outputs at the local electronic device and/or at one or more proximate electronic devices 810 is in sync with software application/module events, user actions, and/or the current state of the local electronic device (e.g., increasing a duration of the adjustment of audio signal outputs when a user continues a digital assistant dialog session by providing a follow-up voice input/digital assistant request). This in turn improves a user's experience with the local electronic device and/or proximate electronic devices 810.
For example, returning to
Returning to
For example, as shown in
As shown in
If local audio adjustment module 814 determines that the local electronic device is currently outputting an audio signal (e.g., as illustrated in
For example, as shown in
6. Processes for Adjusting the Output of Audio Signals at One or More Electronic Devices
At block 1102, a first electronic device (e.g., user device 902 or user device 1002) generates a local audio intent object associated with a software application stored on the first electronic device (e.g., a local application 802 of user device 902), wherein the local audio intent object includes one or more local audio parameters. In some examples, the local audio intent is generated by the software application. In some examples, the software application is a digital assistant module (e.g., digital assistant application 802A) of the first electronic device (e.g., the local audio intent object is generated in response to a user of the first electronic device (e.g., user 906) initiating a digital assistant dialog session (e.g., via a voice input that includes a digital assistant trigger phrase or word (e.g., voice input 904), or via a button press)). In some examples, the software application is a third-party software application (e.g., Google Calendar). In some examples, the local audio adjustment parameters include a local audio adjustment start time, a local audio adjustment duration, and/or one or more application-specific adjustment parameters (e.g., a type of audio adjustment requested by the software application (e.g., stopping the output of an active audio signal, lowering a volume level of the output of an audio signal, filtering the audio signal with low pass, band pass, and/or high pass filters, and/or the like)).
At block 1104, the first electronic device (e.g., proximate intentions module 808 of user device 902) determines that a second electronic device (e.g., smart speaker 908 or smart speaker 1008) is proximate to (e.g., nearby (e.g., in the same room or area)) the first electronic device, wherein the second electronic device is outputting an audio signal (e.g., music audio signals 910 (e.g., via one or more speakers of the second electronic device and/or via one or more speakers that are communicatively connected (e.g., via Wi-Fi, BTLE, or the like) to the second electronic device)). In some examples, electronic devices that are proximate to the first electronic device are predetermined (e.g., based on data and/or information included in a software application stored on the first electronic device (e.g., HomeKit), a website, or the like). In some examples, the first electronic device determines that the second electronic device is proximate to the first electronic device based on one or more signals (e.g., proximity information) received from the second electronic device. In some examples, the first electronic device determines whether there are any electronic devices proximate to the first electronic device in response to generating the local audio intent object. In some examples, the first electronic device periodically determines whether there are any electronic devices proximate to the first electronic device (e.g., every 5 seconds, every 30 seconds, every minute, or the like (e.g., in addition to, or instead of, doing so in response to generating the local audio intent object)).
In some examples, the first electronic device (e.g., proximate intentions module 808 of user device 902) determines that the second electronic device is a proximate electronic device based on predefined data indicating that the second electronic device is a proximate electronic device (e.g., retrieved from a software application stored on the first electronic device (e.g., HomeKit), a website accessible by the first electronic device, or the like). In some examples, the first electronic device (e.g., proximate intentions module 808 of user device 902) determines that the second electronic device is a proximate electronic device based on proximity information determined based on one or more signals received from the second electronic device (e.g., based on data/information included in the one or more signals (e.g., digital assistant trigger detection data/information)). In some of these examples, the first electronic device receives the one or more signals via at least one of a near-field communication connection, a short-range communication connection (e.g., ultra-wideband (UWB), Bluetooth, and/or BTLE signals), and a Wi-Fi connection (e.g., network(s) 909).
In some examples, at block 1106, the first electronic device (e.g., local audio adjustment module 814 and local audio system 816 of user device 902) adjusts the output of a second audio signal being output by the first electronic device based on a local audio adjustment start time included in the one or more local audio adjustment parameters (after transmitting the proximate audio intent object to the second electronic device, when the second electronic device adjusts the audio signal, etc.). In some of these examples, the first electronic device is outputting the second audio signal when the software application generates the local audio intent object. In some examples, the second audio signal is the same as the audio signal output by the second electronic device. In some examples, the second audio signal and the audio signal output by the second electronic device are two distinct audio signals.
In some examples, at block 1108, the first electronic device (e.g., local audio adjustment module 814 and local audio system 816 of user device 902) ends the adjustment of the output of the second audio signal based on a local audio adjustment duration included in the one or more local audio adjustment parameters.
In some examples, at block 1110, the first electronic device generates a second local audio intent object associated with a second software application stored on the first electronic device (e.g., a second local application 802). In some examples, the second software application is the software application (e.g., digital assistant application 802A). In some examples, the second local audio intent object is generated before the local audio intent object is generated. In some examples, the second local audio intent object is generated after the local audio intent object is generated (e.g., but before the proximate audio intent object is generated).
In some examples, at block 1112, the first electronic device (e.g., baseline intention module 812 of user device 902) determines a baseline audio adjustment intention based on the one or more local audio adjustment parameters of the local audio intent object and one or more local audio adjustment parameters of the second local audio intent object. In some of these examples, the proximate audio intent object (described below with reference to block 1116) is generated further based on the baseline audio adjustment intention.
In some examples, the baseline audio adjustment intention includes a baseline audio adjustment start time and a baseline audio adjustment duration. In some examples, the one or more local audio adjustment parameters of the local audio intent object includes a first local audio adjustment start time, the one or more local audio adjustment parameters of the second local audio intent object includes a second local audio adjustment start time, and the baseline audio adjustment start time corresponds to an earlier of the first local audio adjustment start time and the second local audio adjustment start time. In some examples, the one or more local audio adjustment parameters of the local audio intent object includes a first local audio adjustment duration, the one or more local audio adjustment parameters of the second local audio intent object includes a second local audio adjustment duration, and the baseline audio adjustment duration corresponds to a greater (e.g., longer) of the first local audio adjustment duration and the second local audio adjustment duration.
In some examples, at block 1114, the first electronic device (e.g., local audio adjustment module 814 and local audio system 816 of user device 902) adjusts the output of a third audio signal being output by the first electronic device based on the baseline audio adjustment intention (e.g., based on a baseline audio adjustment start time and/or a baseline audio adjustment duration included in the baseline audio adjustment intention). In some of these examples, the first electronic device is outputting the third audio signal when the second local audio intent object is generated. In some examples, the third audio signal is the second audio signal.
At block 1116, the first electronic device (e.g., proximate intentions module 808 of user device 902) generates a proximate audio intent object corresponding to the second electronic device based on the one or more local audio adjustment parameters and a round-trip time (RTT) (e.g., a ping time) of a communication connection (e.g., network(s) 909 (e.g., a near-field communication connection, a short-range communication connection (e.g., ultra-wideband (UWB), Bluetooth, and/or BTLE connection), and/or a Wi-Fi connection)) between the first electronic device and the second electronic device. In some examples, the first electronic device generates the proximate audio intent object in response to determining that the second electronic device is proximate to the first electronic device. In some examples, the first electronic device generates the proximate audio intent object further based on a current state (e.g., user interface responsiveness) of the second electronic device.
In some examples, the proximate audio intent object includes one or more proximate audio adjustment parameters. In some examples, the one or more proximate audio adjustment parameters include a proximate audio adjustment duration. In some examples, the proximate audio adjustment duration is a period of time during which the second electronic device adjusts the output of the audio signal (e.g., based on the proximate audio intent object). In some examples, a value of the proximate audio adjustment duration is greater than (e.g., longer than) a value of the keep-alive time (e.g., a keep-alive time of 4 seconds and a proximate audio adjustment duration of 8 seconds).
In some examples, at block 1118, generating the proximate audio intent object corresponding to the second electronic device includes determining a keep-alive time based on the one or more local audio adjustment parameters and the RTT of the communication connection (e.g., a keep-alive time corresponding to the second electronic device). In some examples, the keep-alive time is generated further based on a current state (e.g., user interface responsiveness) of the second electronic device. In some examples, the keep-alive time is a period of time after the first electronic device transmits the proximate audio intent object to the second electronic device (e.g., 2 seconds, 4 seconds, 8 seconds, or the like). In some examples, after the keep-alive time has elapsed (e.g., immediately after, 1-2 seconds after, or the like), the first electronic device transmits, to the second electronic device, a second proximate audio intent object corresponding to the second electronic device. In some examples, the second proximate audio intent object is identical to the first proximate audio intent object (e.g., same proximate audio adjustment parameters. In some examples, one or more proximate audio adjustment parameters of the second proximate audio intent object are different from corresponding proximate audio adjustment parameters of the first proximate audio intent object.
At block 1120, the first electronic device (e.g., proximate intentions module of user device 902) transmits the proximate audio intent object to the second electronic device via the communication connection (e.g., via network(s) 909), wherein the proximate audio intent object causes the second electronic device to adjust the output of the audio signal (e.g., based on one or more proximate audio adjustment parameters included in the proximate audio intent object (e.g., based on a proximate audio adjustment start time and/or a proximate audio adjustment duration)) (e.g., as described above with reference to
In some the examples described above where the first electronic device is outputting an audio signal, the first electronic device and the second electronic device concurrently adjust (e.g., at the same time or at about the same time) their respective audio signals. In some of these examples, the first electronic device and the second electronic device concurrently end (e.g., at the same time or at about the same time) the adjustment of their respective audio signals.
In some of the examples described above where the first electronic device determines a baseline audio adjustment intention (e.g., at block 1112) and where the first electronic device determines a keep-alive time corresponding to the second electronic device (e.g., at block 1118), at block 1122, the first electronic device generates a third local audio intent object associated with a third software application stored on the first electronic device (e.g., a local application 802 stored on user device 902). In some examples, the third software application is the software application and/or the second software application.
In some examples, at block 1124, the first electronic device (e.g., baseline intention module 812 of user device 902) determines a second baseline audio adjustment intention based on the one or more local audio adjustment parameters of the local audio intent object and one or more local audio adjustment parameters of the third local audio intent object.
In some examples, at block 1126, the first electronic device (e.g., proximate intentions module 808 of user device 902) generates a third proximate audio intent object based on the second baseline audio adjustment intention. In some of these examples, at least one proximate audio adjustment parameter included in the third proximate audio intent object (e.g., proximate audio adjustment duration) is different than (e.g., longer or shorter than) a corresponding proximate audio adjustment parameter included in the proximate audio intent object.
In some examples, at block 1128, generating the third local audio intent object includes the first electronic device (e.g., proximate intentions module 808 of user device 902) determining a second keep-alive time based on the second baseline audio adjustment intention (e.g., based on baseline audio adjustment start time and/or a baseline audio adjustment duration included in the second baseline audio intention) and the RTT of the communication connection.
In some examples, at block 1130, the first electronic device transmits the third proximate audio intent object to the second electronic device when the keep-alive time elapses (e.g., immediately after the keep-alive time elapses, 1 or 2 seconds after the keep-alive time elapses, or the like).
In some examples, at block 1132, the first electronic device (e.g., user device 1002) outputs a fourth audio signal (e.g., music audio signals 1004). In some of these examples, at block 1134, the first electronic device (e.g., remote intentions module 818 of user device 1002) receives a remote audio intent object from a third electronic device, wherein the remote audio intent object includes one or more remote audio adjustment parameters. In some examples, the third electronic device is the second electronic device. In some examples, the third electronic device is proximate to the first electronic device.
In some examples, at block 1136, the first electronic device (e.g., local audio adjustment module 814 and local audio system 816 of user device 1002) adjusts the output of the fourth audio signal based on the one or more remote audio adjustment parameters (e.g., as described above with reference to
The operations described above with reference to
In accordance with some implementations, a computer-readable storage medium (e.g., a non-transitory computer readable storage medium) is provided, the computer-readable storage medium storing one or more programs for execution by one or more processors of an electronic device, the one or more programs including instructions for performing any of the methods or processes described herein.
In accordance with some implementations, an electronic device (e.g., a portable electronic device) is provided that comprises means for performing any of the methods or processes described herein.
In accordance with some implementations, an electronic device (e.g., a portable electronic device) is provided that comprises a processing unit configured to perform any of the methods or processes described herein.
In accordance with some implementations, an electronic device (e.g., a portable electronic device) is provided that comprises one or more processors and memory storing one or more programs for execution by the one or more processors, the one or more programs including instructions for performing any of the methods or processes described herein.
The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The embodiments were chosen and described in order to best explain the principles of the techniques and their practical applications. Others skilled in the art are thereby enabled to best utilize the techniques and various embodiments with various modifications as are suited to the particular use contemplated.
Although the disclosure and examples have been fully described with reference to the accompanying drawings, it is to be noted that various changes and modifications will become apparent to those skilled in the art. Such changes and modifications are to be understood as being included within the scope of the disclosure and examples as defined by the claims.
As described above, one aspect of the present technology is the gathering and use of data (e.g., user-specific context information) available from various sources to assist with/improve the determination of digital assistant responses for user commands and requests. 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, twitter IDs, home addresses, data or records relating to a user's health or level of fitness (e.g., vital signs measurements, medication information, exercise information), date of birth, or any other identifying or personal 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 determine one or more parameters of a task to be performed by digital assistant of a user device. Accordingly, use of such personal information data enables a digital assistant of a user device to provide a digital assistant response (based on the performance of the above task) that is more relevant and/or useful to users. Further, other uses for personal information data that benefit the user are also contemplated by the present disclosure. For instance, health and fitness data may be used to provide insights into a user's general wellness, or may be used as positive feedback to individuals using technology to pursue wellness goals.
The present disclosure 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. Such policies should be easily accessible by users, and should be updated as the collection and/or use of data changes. 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/sharing should occur after receiving the informed consent of the users. Additionally, such entities should consider taking 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. In addition, policies and practices should be adapted for the particular types of personal information data being collected and/or accessed and adapted to applicable laws and standards, including jurisdiction-specific considerations. For instance, in the US, collection of or access to certain health data may be governed by federal and/or state laws, such as the Health Insurance Portability and Accountability Act (HIPAA); whereas health data in other countries may be subject to other regulations and policies and should be handled accordingly. Hence different privacy practices should be maintained for different personal data types in each country.
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 gathering and using user-specific context information to assist with/improve the determination of digital assistant responses, 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 or anytime thereafter. In another example, users can select not to provide user-specific context information to assist with/improve the determination of digital assistant responses. In yet another example, users can select to prevent the gathering and use of certain types/forms of user-specific context information (e.g., home addresses, email addresses, phone numbers, location data, or the like) for the determination of digital assistant responses. In addition to providing “opt in” and “opt out” options, the present disclosure contemplates providing notifications relating to the access or use of personal information. For instance, a user may be notified upon downloading an app that their personal information data will be accessed and then reminded again just before personal information data is accessed by the app.
Moreover, it is the intent of the present disclosure that personal information data should be managed and handled in a way to minimize risks of unintentional or unauthorized access or use. Risk can be minimized by limiting the collection of data and deleting data once it is no longer needed. In addition, and when applicable, including in certain health related applications, data de-identification can be used to protect a user's privacy. De-identification may be facilitated, when appropriate, by removing specific identifiers (e.g., date of birth, etc.), controlling the amount or specificity of data stored (e.g., collecting location data at a city level rather than at an address level), controlling how data is stored (e.g., aggregating data across users), and/or other methods.
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, digital assistant responses can be determined 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 digital assistant, or publicly available information.
This application is a continuation of U.S. patent application Ser. No. 17/131,267, entitled “MULTI-DEVICE AUDIO ADJUSTMENT COORDINATION,” filed Dec. 22, 2020, which claims the benefit of U.S. Provisional Patent Application No. 63/054,178, entitled “MULTI-DEVICE AUDIO ADJUSTMENT COORDINATION,” filed Jul. 20, 2020, the contents of which are hereby incorporated by reference in their entirety for all purposes.
| Number | Name | Date | Kind |
|---|---|---|---|
| 7596269 | King | Sep 2009 | B2 |
| 8090571 | Elshishiny et al. | Jan 2012 | B2 |
| 8095364 | Longe et al. | Jan 2012 | B2 |
| 8099289 | Mozer et al. | Jan 2012 | B2 |
| 8099395 | Pabla et al. | Jan 2012 | B2 |
| 8099418 | Inoue et al. | Jan 2012 | B2 |
| 8103510 | Sato | Jan 2012 | B2 |
| 8103947 | Lunt et al. | Jan 2012 | B2 |
| 8107401 | John et al. | Jan 2012 | B2 |
| 8112275 | Kennewick et al. | Feb 2012 | B2 |
| 8112280 | Lu | Feb 2012 | B2 |
| 8115772 | Ostermann et al. | Feb 2012 | B2 |
| 8117026 | Lee et al. | Feb 2012 | B2 |
| 8117037 | Gazdzinski | Feb 2012 | B2 |
| 8117542 | Radtke et al. | Feb 2012 | B2 |
| 8121413 | Hwang et al. | Feb 2012 | B2 |
| 8121837 | Agapi et al. | Feb 2012 | B2 |
| 8122094 | Kotab | Feb 2012 | B1 |
| 8122353 | Bouta | Feb 2012 | B2 |
| 8130929 | Wilkes et al. | Mar 2012 | B2 |
| 8131556 | Barton et al. | Mar 2012 | B2 |
| 8131557 | Davis et al. | Mar 2012 | B2 |
| 8135115 | Hogg, Jr. et al. | Mar 2012 | B1 |
| 8138912 | Singh et al. | Mar 2012 | B2 |
| 8140330 | Cevik et al. | Mar 2012 | B2 |
| 8140335 | Kennewick et al. | Mar 2012 | B2 |
| 8140368 | Eggenberger et al. | Mar 2012 | B2 |
| 8140567 | Padovitz et al. | Mar 2012 | B2 |
| 8145489 | Freeman et al. | Mar 2012 | B2 |
| 8150694 | Kennewick et al. | Apr 2012 | B2 |
| 8150700 | Shin et al. | Apr 2012 | B2 |
| 8155956 | Cho et al. | Apr 2012 | B2 |
| 8156005 | Vieri | Apr 2012 | B2 |
| 8156060 | Borzestowski et al. | Apr 2012 | B2 |
| 8160877 | Nucci et al. | Apr 2012 | B1 |
| 8160883 | Lecoeuche | Apr 2012 | B2 |
| 8165321 | Paquier et al. | Apr 2012 | B2 |
| 8165886 | Gagnon et al. | Apr 2012 | B1 |
| 8166019 | Lee et al. | Apr 2012 | B1 |
| 8166032 | Sommer et al. | Apr 2012 | B2 |
| 8170790 | Lee et al. | May 2012 | B2 |
| 8170966 | Musat et al. | May 2012 | B1 |
| 8171137 | Parks et al. | May 2012 | B1 |
| 8175872 | Kristjansson et al. | May 2012 | B2 |
| 8175876 | Bou-Ghazale et al. | May 2012 | B2 |
| 8179370 | Yamasani et al. | May 2012 | B1 |
| 8188856 | Singh et al. | May 2012 | B2 |
| 8190359 | Bourne | May 2012 | B2 |
| 8190596 | Nambiar et al. | May 2012 | B2 |
| 8194827 | Jaiswal et al. | Jun 2012 | B2 |
| 8195467 | Mozer et al. | Jun 2012 | B2 |
| 8195468 | Weider et al. | Jun 2012 | B2 |
| 8200489 | Baggenstoss | Jun 2012 | B1 |
| 8200495 | Braho et al. | Jun 2012 | B2 |
| 8201109 | Van Os et al. | Jun 2012 | B2 |
| 8204238 | Mozer | Jun 2012 | B2 |
| 8204751 | Di et al. | Jun 2012 | B1 |
| 8205788 | Gazdzinski et al. | Jun 2012 | B1 |
| 8209177 | Sakuma et al. | Jun 2012 | B2 |
| 8209183 | Patel et al. | Jun 2012 | B1 |
| 8213911 | Williams et al. | Jul 2012 | B2 |
| 8219115 | Nelissen | Jul 2012 | B1 |
| 8219406 | Yu et al. | Jul 2012 | B2 |
| 8219407 | Roy et al. | Jul 2012 | B1 |
| 8219555 | Mianji | Jul 2012 | B1 |
| 8219608 | alSafadi et al. | Jul 2012 | B2 |
| 8224649 | Chaudhari et al. | Jul 2012 | B2 |
| 8224757 | Bohle | Jul 2012 | B2 |
| 8228299 | Maloney et al. | Jul 2012 | B1 |
| 8233919 | Haag et al. | Jul 2012 | B2 |
| 8234111 | Lloyd et al. | Jul 2012 | B2 |
| 8239206 | LeBeau et al. | Aug 2012 | B1 |
| 8239207 | Seligman et al. | Aug 2012 | B2 |
| 8244545 | Paek et al. | Aug 2012 | B2 |
| 8244672 | Thenthiruperai et al. | Aug 2012 | B1 |
| 8244712 | Serlet et al. | Aug 2012 | B2 |
| 8250071 | Killalea et al. | Aug 2012 | B1 |
| 8254829 | Kindred et al. | Aug 2012 | B1 |
| 8255216 | White | Aug 2012 | B2 |
| 8255217 | Stent et al. | Aug 2012 | B2 |
| 8260117 | Xu et al. | Sep 2012 | B1 |
| 8260247 | Lazaridis et al. | Sep 2012 | B2 |
| 8260617 | Dhanakshirur et al. | Sep 2012 | B2 |
| 8260619 | Bansal et al. | Sep 2012 | B1 |
| 8270933 | Riemer et al. | Sep 2012 | B2 |
| 8271287 | Kermani | Sep 2012 | B1 |
| 8275621 | Alewine et al. | Sep 2012 | B2 |
| 8275736 | Guo et al. | Sep 2012 | B2 |
| 8279171 | Hirai et al. | Oct 2012 | B2 |
| 8280438 | Barbera | Oct 2012 | B2 |
| 8285546 | Reich | Oct 2012 | B2 |
| 8285551 | Gazdzinski | Oct 2012 | B2 |
| 8285553 | Gazdzinski | Oct 2012 | B2 |
| 8285737 | Lynn et al. | Oct 2012 | B1 |
| 8290274 | Mori et al. | Oct 2012 | B2 |
| 8290777 | Nguyen et al. | Oct 2012 | B1 |
| 8290778 | Gazdzinski | Oct 2012 | B2 |
| 8290781 | Gazdzinski | Oct 2012 | B2 |
| 8296124 | Holsztynska et al. | Oct 2012 | B1 |
| 8296145 | Clark et al. | Oct 2012 | B2 |
| 8296146 | Gazdzinski | Oct 2012 | B2 |
| 8296153 | Gazdzinski | Oct 2012 | B2 |
| 8296380 | Kelly et al. | Oct 2012 | B1 |
| 8296383 | Lindahl | Oct 2012 | B2 |
| 8300776 | Davies et al. | Oct 2012 | B2 |
| 8300801 | Sweeney et al. | Oct 2012 | B2 |
| 8301456 | Gazdzinski | Oct 2012 | B2 |
| 8311189 | Champlin et al. | Nov 2012 | B2 |
| 8311834 | Gazdzinski | Nov 2012 | B1 |
| 8311835 | Lecoeuche | Nov 2012 | B2 |
| 8311838 | Lindahl et al. | Nov 2012 | B2 |
| 8312017 | Martin et al. | Nov 2012 | B2 |
| 8321786 | Lunati | Nov 2012 | B2 |
| 8326627 | Kennewick et al. | Dec 2012 | B2 |
| 8332205 | Krishnan et al. | Dec 2012 | B2 |
| 8332218 | Cross, Jr. et al. | Dec 2012 | B2 |
| 8332224 | Di Cristo et al. | Dec 2012 | B2 |
| 8332748 | Karam | Dec 2012 | B1 |
| 8335689 | Wittenstein et al. | Dec 2012 | B2 |
| 8340975 | Rosenberger | Dec 2012 | B1 |
| 8345665 | Vieri et al. | Jan 2013 | B2 |
| 8346563 | Hjelm et al. | Jan 2013 | B1 |
| 8346757 | Lamping et al. | Jan 2013 | B1 |
| 8352183 | Thota et al. | Jan 2013 | B2 |
| 8352268 | Naik et al. | Jan 2013 | B2 |
| 8352272 | Rogers et al. | Jan 2013 | B2 |
| 8355919 | Silverman et al. | Jan 2013 | B2 |
| 8359234 | Vieri | Jan 2013 | B2 |
| 8370145 | Endo et al. | Feb 2013 | B2 |
| 8370158 | Gazdzinski | Feb 2013 | B2 |
| 8371503 | Gazdzinski | Feb 2013 | B2 |
| 8374871 | Ehsani et al. | Feb 2013 | B2 |
| 8375320 | Kotler et al. | Feb 2013 | B2 |
| 8380504 | Peden et al. | Feb 2013 | B1 |
| 8380507 | Herman et al. | Feb 2013 | B2 |
| 8381107 | Rottler et al. | Feb 2013 | B2 |
| 8381135 | Hotelling et al. | Feb 2013 | B2 |
| 8386485 | Kerschberg et al. | Feb 2013 | B2 |
| 8386926 | Matsuoka et al. | Feb 2013 | B1 |
| 8391844 | Novick et al. | Mar 2013 | B2 |
| 8392717 | Chai et al. | Mar 2013 | B2 |
| 8396295 | Gao et al. | Mar 2013 | B2 |
| 8396714 | Rogers et al. | Mar 2013 | B2 |
| 8396715 | Odell et al. | Mar 2013 | B2 |
| 8401163 | Kirchhoff et al. | Mar 2013 | B1 |
| 8406745 | Upadhyay et al. | Mar 2013 | B1 |
| 8407239 | Dean et al. | Mar 2013 | B2 |
| 8423288 | Stahl et al. | Apr 2013 | B2 |
| 8428758 | Naik et al. | Apr 2013 | B2 |
| 8433572 | Caskey et al. | Apr 2013 | B2 |
| 8433778 | Shreesha et al. | Apr 2013 | B1 |
| 8434133 | Kulkarni et al. | Apr 2013 | B2 |
| 8442821 | Vanhoucke | May 2013 | B1 |
| 8447612 | Gazdzinski | May 2013 | B2 |
| 8452597 | Bringert et al. | May 2013 | B2 |
| 8452602 | Bringert et al. | May 2013 | B1 |
| 8453058 | Coccaro et al. | May 2013 | B1 |
| 8457959 | Kaiser | Jun 2013 | B2 |
| 8458115 | Cai et al. | Jun 2013 | B2 |
| 8458278 | Christie et al. | Jun 2013 | B2 |
| 8463592 | Lu et al. | Jun 2013 | B2 |
| 8464150 | Davidson et al. | Jun 2013 | B2 |
| 8473289 | Jitkoff et al. | Jun 2013 | B2 |
| 8473485 | Wong et al. | Jun 2013 | B2 |
| 8477323 | Low et al. | Jul 2013 | B2 |
| 8478816 | Parks et al. | Jul 2013 | B2 |
| 8479122 | Hotelling et al. | Jul 2013 | B2 |
| 8484027 | Murphy | Jul 2013 | B1 |
| 8489599 | Bellotti | Jul 2013 | B2 |
| 8498670 | Cha et al. | Jul 2013 | B2 |
| 8498857 | Kopparapu et al. | Jul 2013 | B2 |
| 8514197 | Shahraray et al. | Aug 2013 | B2 |
| 8515736 | Duta | Aug 2013 | B1 |
| 8515750 | Lei et al. | Aug 2013 | B1 |
| 8521513 | Millett et al. | Aug 2013 | B2 |
| 8521526 | Lloyd et al. | Aug 2013 | B1 |
| 8521531 | Kim | Aug 2013 | B1 |
| 8521533 | Ostermann et al. | Aug 2013 | B1 |
| 8527276 | Senior et al. | Sep 2013 | B1 |
| 8533266 | Koulomzin et al. | Sep 2013 | B2 |
| 8537033 | Gueziec | Sep 2013 | B2 |
| 8539342 | Lewis | Sep 2013 | B1 |
| 8543375 | Hong | Sep 2013 | B2 |
| 8543397 | Nguyen | Sep 2013 | B1 |
| 8543398 | Strope et al. | Sep 2013 | B1 |
| 8560229 | Park et al. | Oct 2013 | B1 |
| 8560366 | Mikurak | Oct 2013 | B2 |
| 8571528 | Channakeshava | Oct 2013 | B1 |
| 8571851 | Tickner et al. | Oct 2013 | B1 |
| 8577683 | Dewitt | Nov 2013 | B2 |
| 8583416 | Huang et al. | Nov 2013 | B2 |
| 8583511 | Hendrickson | Nov 2013 | B2 |
| 8583638 | Donelli | Nov 2013 | B2 |
| 8589156 | Burke et al. | Nov 2013 | B2 |
| 8589161 | Kennewick et al. | Nov 2013 | B2 |
| 8589374 | Chaudhari | Nov 2013 | B2 |
| 8589869 | Wolfram | Nov 2013 | B2 |
| 8589911 | Sharkey et al. | Nov 2013 | B1 |
| 8595004 | Koshinaka | Nov 2013 | B2 |
| 8595642 | Lagassey | Nov 2013 | B1 |
| 8600743 | Lindahl et al. | Dec 2013 | B2 |
| 8600746 | Lei et al. | Dec 2013 | B1 |
| 8600930 | Sata et al. | Dec 2013 | B2 |
| 8606090 | Eyer | Dec 2013 | B2 |
| 8606568 | Tickner et al. | Dec 2013 | B1 |
| 8606576 | Barr et al. | Dec 2013 | B1 |
| 8606577 | Stewart et al. | Dec 2013 | B1 |
| 8615221 | Cosenza et al. | Dec 2013 | B1 |
| 8620659 | Di Cristo et al. | Dec 2013 | B2 |
| 8620662 | Bellegarda | Dec 2013 | B2 |
| 8626681 | Jurca et al. | Jan 2014 | B1 |
| 8630841 | Van Caldwell et al. | Jan 2014 | B2 |
| 8635073 | Chang | Jan 2014 | B2 |
| 8638363 | King et al. | Jan 2014 | B2 |
| 8639516 | Lindahl et al. | Jan 2014 | B2 |
| 8645128 | Agiomyrgiannakis | Feb 2014 | B1 |
| 8645137 | Bellegarda et al. | Feb 2014 | B2 |
| 8645138 | Weinstein et al. | Feb 2014 | B1 |
| 8654936 | Eslambolchi et al. | Feb 2014 | B1 |
| 8655646 | Lee et al. | Feb 2014 | B2 |
| 8655901 | Li et al. | Feb 2014 | B1 |
| 8660843 | Falcon et al. | Feb 2014 | B2 |
| 8660849 | Gruber et al. | Feb 2014 | B2 |
| 8660924 | Hoch et al. | Feb 2014 | B2 |
| 8660970 | Fiedorowicz | Feb 2014 | B1 |
| 8661112 | Creamer et al. | Feb 2014 | B2 |
| 8661340 | Goldsmith et al. | Feb 2014 | B2 |
| 8670979 | Gruber et al. | Mar 2014 | B2 |
| 8675084 | Bolton et al. | Mar 2014 | B2 |
| 8676273 | Fujisaki | Mar 2014 | B1 |
| 8676583 | Gupta et al. | Mar 2014 | B2 |
| 8676904 | Lindahl | Mar 2014 | B2 |
| 8677377 | Cheyer et al. | Mar 2014 | B2 |
| 8681950 | Mack et al. | Mar 2014 | B2 |
| 8682667 | Haughay | Mar 2014 | B2 |
| 8687777 | Lavian et al. | Apr 2014 | B1 |
| 8688446 | Yanagihara | Apr 2014 | B2 |
| 8688453 | Joshi et al. | Apr 2014 | B1 |
| 8689135 | Portele et al. | Apr 2014 | B2 |
| 8694322 | Snitkovskiy et al. | Apr 2014 | B2 |
| 8695074 | Saraf et al. | Apr 2014 | B2 |
| 8696364 | Cohen | Apr 2014 | B2 |
| 8706472 | Ramerth et al. | Apr 2014 | B2 |
| 8706474 | Blume et al. | Apr 2014 | B2 |
| 8706503 | Cheyer et al. | Apr 2014 | B2 |
| 8707195 | Fleizach et al. | Apr 2014 | B2 |
| 8712778 | Thenthiruperai | Apr 2014 | B1 |
| 8713119 | Lindahl et al. | Apr 2014 | B2 |
| 8713418 | King et al. | Apr 2014 | B2 |
| 8719006 | Bellegarda | May 2014 | B2 |
| 8719014 | Wagner | May 2014 | B2 |
| 8719039 | Sharifi | May 2014 | B1 |
| 8731610 | Appaji | May 2014 | B2 |
| 8731912 | Tickner et al. | May 2014 | B1 |
| 8731942 | Cheyer et al. | May 2014 | B2 |
| 8739208 | Davis et al. | May 2014 | B2 |
| 8744852 | Seymour et al. | Jun 2014 | B1 |
| 8751971 | Fleizach et al. | Jun 2014 | B2 |
| 8760537 | Johnson et al. | Jun 2014 | B2 |
| 8762145 | Ouchi et al. | Jun 2014 | B2 |
| 8762156 | Chen | Jun 2014 | B2 |
| 8762469 | Lindahl | Jun 2014 | B2 |
| 8768693 | Somekh et al. | Jul 2014 | B2 |
| 8768702 | Mason et al. | Jul 2014 | B2 |
| 8775154 | Clinchant et al. | Jul 2014 | B2 |
| 8775177 | Heigold et al. | Jul 2014 | B1 |
| 8775341 | Commons | Jul 2014 | B1 |
| 8775931 | Fux et al. | Jul 2014 | B2 |
| 8781456 | Prociw | Jul 2014 | B2 |
| 8781841 | Wang | Jul 2014 | B1 |
| 8793301 | Wegenkittl et al. | Jul 2014 | B2 |
| 8798255 | Lubowich et al. | Aug 2014 | B2 |
| 8798995 | Edara | Aug 2014 | B1 |
| 8799000 | Guzzoni et al. | Aug 2014 | B2 |
| 8805684 | Aleksic et al. | Aug 2014 | B1 |
| 8805690 | Lebeau et al. | Aug 2014 | B1 |
| 8812299 | Su | Aug 2014 | B1 |
| 8812302 | Xiao et al. | Aug 2014 | B2 |
| 8812321 | Gilbert et al. | Aug 2014 | B2 |
| 8823507 | Touloumtzis | Sep 2014 | B1 |
| 8823793 | Clayton et al. | Sep 2014 | B2 |
| 8825474 | Zhai et al. | Sep 2014 | B1 |
| 8831947 | Wasserblat et al. | Sep 2014 | B2 |
| 8831949 | Smith et al. | Sep 2014 | B1 |
| 8838457 | Cerra et al. | Sep 2014 | B2 |
| 8855915 | Furuhata et al. | Oct 2014 | B2 |
| 8861925 | Ohme | Oct 2014 | B1 |
| 8862252 | Rottler et al. | Oct 2014 | B2 |
| 8868111 | Kahn et al. | Oct 2014 | B1 |
| 8868409 | Mengibar et al. | Oct 2014 | B1 |
| 8868431 | Yamazaki et al. | Oct 2014 | B2 |
| 8868469 | Xu et al. | Oct 2014 | B2 |
| 8868529 | Lerenc | Oct 2014 | B2 |
| 8880405 | Cerra et al. | Nov 2014 | B2 |
| 8886534 | Nakano et al. | Nov 2014 | B2 |
| 8886540 | Cerra et al. | Nov 2014 | B2 |
| 8886541 | Friedlander | Nov 2014 | B2 |
| 8892446 | Cheyer et al. | Nov 2014 | B2 |
| 8893023 | Perry et al. | Nov 2014 | B2 |
| 8897822 | Martin | Nov 2014 | B2 |
| 8898064 | Thomas et al. | Nov 2014 | B1 |
| 8898568 | Bull et al. | Nov 2014 | B2 |
| 8903716 | Chen et al. | Dec 2014 | B2 |
| 8909693 | Frissora et al. | Dec 2014 | B2 |
| 8918321 | Czahor | Dec 2014 | B2 |
| 8922485 | Lloyd | Dec 2014 | B1 |
| 8930176 | Li et al. | Jan 2015 | B2 |
| 8930191 | Gruber et al. | Jan 2015 | B2 |
| 8938394 | Faaborg et al. | Jan 2015 | B1 |
| 8938450 | Spivack et al. | Jan 2015 | B2 |
| 8938688 | Bradford et al. | Jan 2015 | B2 |
| 8942986 | Cheyer et al. | Jan 2015 | B2 |
| 8943423 | Merrill et al. | Jan 2015 | B2 |
| 8964947 | Noolu et al. | Feb 2015 | B1 |
| 8965770 | Petrushin | Feb 2015 | B2 |
| 8972240 | Brockett et al. | Mar 2015 | B2 |
| 8972432 | Shaw et al. | Mar 2015 | B2 |
| 8972878 | Mohler et al. | Mar 2015 | B2 |
| 8976063 | Hawkins et al. | Mar 2015 | B1 |
| 8976108 | Hawkins et al. | Mar 2015 | B2 |
| 8977255 | Freeman et al. | Mar 2015 | B2 |
| 8983383 | Haskin | Mar 2015 | B1 |
| 8984098 | Tomkins et al. | Mar 2015 | B1 |
| 8989713 | Doulton | Mar 2015 | B2 |
| 8990235 | King et al. | Mar 2015 | B2 |
| 8994660 | Neels et al. | Mar 2015 | B2 |
| 8995972 | Cronin | Mar 2015 | B1 |
| 8996350 | Dub et al. | Mar 2015 | B1 |
| 8996376 | Fleizach et al. | Mar 2015 | B2 |
| 8996381 | Mozer et al. | Mar 2015 | B2 |
| 8996550 | Ko et al. | Mar 2015 | B2 |
| 8996639 | Faaborg et al. | Mar 2015 | B1 |
| 9002714 | Kim et al. | Apr 2015 | B2 |
| 9009046 | Stewart | Apr 2015 | B1 |
| 9015036 | Karov Zangvil et al. | Apr 2015 | B2 |
| 9020804 | Barbaiani et al. | Apr 2015 | B2 |
| 9026425 | Nikoulina et al. | May 2015 | B2 |
| 9026426 | Wu et al. | May 2015 | B2 |
| 9031834 | Coorman et al. | May 2015 | B2 |
| 9031970 | Das et al. | May 2015 | B1 |
| 9037967 | Al-Jefri et al. | May 2015 | B1 |
| 9043208 | Koch et al. | May 2015 | B2 |
| 9043211 | Haiut et al. | May 2015 | B2 |
| 9046932 | Medlock et al. | Jun 2015 | B2 |
| 9049255 | Macfarlane et al. | Jun 2015 | B2 |
| 9049295 | Cooper et al. | Jun 2015 | B1 |
| 9053706 | Jitkoff et al. | Jun 2015 | B2 |
| 9058105 | Drory et al. | Jun 2015 | B2 |
| 9058332 | Darby et al. | Jun 2015 | B1 |
| 9058811 | Wang et al. | Jun 2015 | B2 |
| 9063979 | Chiu et al. | Jun 2015 | B2 |
| 9064495 | Torok et al. | Jun 2015 | B1 |
| 9065660 | Ellis et al. | Jun 2015 | B2 |
| 9070247 | Kuhn et al. | Jun 2015 | B2 |
| 9070366 | Mathias et al. | Jun 2015 | B1 |
| 9071701 | Donaldson et al. | Jun 2015 | B2 |
| 9075435 | Noble et al. | Jul 2015 | B1 |
| 9075824 | Gordo et al. | Jul 2015 | B2 |
| 9076448 | Bennett et al. | Jul 2015 | B2 |
| 9076450 | Sadek et al. | Jul 2015 | B1 |
| 9081411 | Kalns et al. | Jul 2015 | B2 |
| 9081482 | Zhai et al. | Jul 2015 | B1 |
| 9082402 | Yadgar et al. | Jul 2015 | B2 |
| 9083581 | Addepalli et al. | Jul 2015 | B1 |
| 9092789 | Anshul | Jul 2015 | B2 |
| 9094576 | Karakotsios | Jul 2015 | B1 |
| 9094636 | Sanders et al. | Jul 2015 | B1 |
| 9098467 | Blanksteen et al. | Aug 2015 | B1 |
| 9101279 | Ritchey et al. | Aug 2015 | B2 |
| 9112984 | Sejnoha et al. | Aug 2015 | B2 |
| 9117212 | Sheets et al. | Aug 2015 | B2 |
| 9117447 | Gruber et al. | Aug 2015 | B2 |
| 9123338 | Sanders et al. | Sep 2015 | B1 |
| 9143907 | Caldwell et al. | Sep 2015 | B1 |
| 9159319 | Hoffmeister | Oct 2015 | B1 |
| 9164983 | Liu et al. | Oct 2015 | B2 |
| 9171541 | Kennewick et al. | Oct 2015 | B2 |
| 9171546 | Pike | Oct 2015 | B1 |
| 9172747 | Walters et al. | Oct 2015 | B2 |
| 9183845 | Gopalakrishnan et al. | Nov 2015 | B1 |
| 9190062 | Haughay | Nov 2015 | B2 |
| 9196245 | Larcheveque et al. | Nov 2015 | B2 |
| 9197848 | Felkai et al. | Nov 2015 | B2 |
| 9201955 | Quintao et al. | Dec 2015 | B1 |
| 9202520 | Tang | Dec 2015 | B1 |
| 9208153 | Zaveri et al. | Dec 2015 | B1 |
| 9213754 | Zhan et al. | Dec 2015 | B1 |
| 9218122 | Thoma et al. | Dec 2015 | B2 |
| 9218809 | Bellegard et al. | Dec 2015 | B2 |
| 9218819 | Stekkelpa et al. | Dec 2015 | B1 |
| 9223537 | Brown et al. | Dec 2015 | B2 |
| 9230561 | Ostermann et al. | Jan 2016 | B2 |
| 9232293 | Hanson | Jan 2016 | B1 |
| 9236047 | Rasmussen | Jan 2016 | B2 |
| 9241073 | Rensburg et al. | Jan 2016 | B1 |
| 9245151 | LeBeau et al. | Jan 2016 | B2 |
| 9250703 | Hernandez-Abrego et al. | Feb 2016 | B2 |
| 9251713 | Giovanniello et al. | Feb 2016 | B1 |
| 9251787 | Hart et al. | Feb 2016 | B1 |
| 9255812 | Maeoka et al. | Feb 2016 | B2 |
| 9257120 | Alvarez Guevara et al. | Feb 2016 | B1 |
| 9258604 | Bilobrov et al. | Feb 2016 | B1 |
| 9262412 | Yang et al. | Feb 2016 | B2 |
| 9262612 | Cheyer | Feb 2016 | B2 |
| 9263058 | Huang et al. | Feb 2016 | B2 |
| 9274598 | Beymer et al. | Mar 2016 | B2 |
| 9280535 | Varma et al. | Mar 2016 | B2 |
| 9282211 | Osawa | Mar 2016 | B2 |
| 9286727 | Kim et al. | Mar 2016 | B2 |
| 9286910 | Li et al. | Mar 2016 | B1 |
| 9292487 | Weber | Mar 2016 | B1 |
| 9292489 | Sak et al. | Mar 2016 | B1 |
| 9292492 | Sarikaya et al. | Mar 2016 | B2 |
| 9298358 | Wilden et al. | Mar 2016 | B1 |
| 9299344 | Braho et al. | Mar 2016 | B2 |
| 9300718 | Khanna | Mar 2016 | B2 |
| 9301256 | Mohan et al. | Mar 2016 | B2 |
| 9305543 | Fleizach et al. | Apr 2016 | B2 |
| 9305548 | Kennewick et al. | Apr 2016 | B2 |
| 9311308 | Sankarasubramaniam et al. | Apr 2016 | B2 |
| 9311912 | Swietlinski et al. | Apr 2016 | B1 |
| 9313317 | LeBeau et al. | Apr 2016 | B1 |
| 9318108 | Gruber et al. | Apr 2016 | B2 |
| 9325809 | Barros et al. | Apr 2016 | B1 |
| 9325842 | Siddiqi et al. | Apr 2016 | B1 |
| 9330659 | Ju et al. | May 2016 | B2 |
| 9330668 | Nanavati et al. | May 2016 | B2 |
| 9330720 | Lee | May 2016 | B2 |
| 9335983 | Breiner et al. | May 2016 | B2 |
| 9338493 | Van Os et al. | May 2016 | B2 |
| 9342829 | Zhou et al. | May 2016 | B2 |
| 9342930 | Kraft et al. | May 2016 | B1 |
| 9349368 | Lebeau et al. | May 2016 | B1 |
| 9355472 | Kocienda et al. | May 2016 | B2 |
| 9361084 | Costa | Jun 2016 | B1 |
| 9367541 | Servan et al. | Jun 2016 | B1 |
| 9368114 | Larson et al. | Jun 2016 | B2 |
| 9377871 | Waddell et al. | Jun 2016 | B2 |
| 9378456 | White et al. | Jun 2016 | B2 |
| 9378740 | Rosen et al. | Jun 2016 | B1 |
| 9380155 | Reding et al. | Jun 2016 | B1 |
| 9383827 | Faaborg et al. | Jul 2016 | B1 |
| 9384185 | Medlock et al. | Jul 2016 | B2 |
| 9390726 | Smus et al. | Jul 2016 | B1 |
| 9396722 | Chung et al. | Jul 2016 | B2 |
| 9400779 | Convertino et al. | Jul 2016 | B2 |
| 9401140 | Weber et al. | Jul 2016 | B1 |
| 9401147 | Jitkoff et al. | Jul 2016 | B2 |
| 9405741 | Schaaf et al. | Aug 2016 | B1 |
| 9406224 | Sanders et al. | Aug 2016 | B1 |
| 9406299 | Gollan et al. | Aug 2016 | B2 |
| 9408182 | Hurley et al. | Aug 2016 | B1 |
| 9412392 | Lindahl | Aug 2016 | B2 |
| 9418650 | Bharadwaj et al. | Aug 2016 | B2 |
| 9423266 | Clark et al. | Aug 2016 | B2 |
| 9424246 | Spencer et al. | Aug 2016 | B2 |
| 9424840 | Hart et al. | Aug 2016 | B1 |
| 9431021 | Scalise et al. | Aug 2016 | B1 |
| 9432499 | Hajdu et al. | Aug 2016 | B2 |
| 9436918 | Pantel et al. | Sep 2016 | B2 |
| 9437186 | Liu et al. | Sep 2016 | B1 |
| 9437189 | Epstein et al. | Sep 2016 | B2 |
| 9442687 | Park et al. | Sep 2016 | B2 |
| 9443527 | Watanabe et al. | Sep 2016 | B1 |
| 9454599 | Golden et al. | Sep 2016 | B2 |
| 9454957 | Mathias et al. | Sep 2016 | B1 |
| 9465798 | Lin | Oct 2016 | B2 |
| 9465833 | Aravamudan et al. | Oct 2016 | B2 |
| 9465864 | Hu et al. | Oct 2016 | B2 |
| 9466027 | Byrne et al. | Oct 2016 | B2 |
| 9466294 | Tunstall-Pedoe et al. | Oct 2016 | B1 |
| 9471566 | Zhang et al. | Oct 2016 | B1 |
| 9472196 | Wang et al. | Oct 2016 | B1 |
| 9483388 | Sankaranarasimhan et al. | Nov 2016 | B2 |
| 9483461 | Fleizach et al. | Nov 2016 | B2 |
| 9483529 | Pasoi et al. | Nov 2016 | B1 |
| 9484021 | Mairesse et al. | Nov 2016 | B1 |
| 9485286 | Sellier et al. | Nov 2016 | B1 |
| 9495129 | Fleizach et al. | Nov 2016 | B2 |
| 9501741 | Cheyer et al. | Nov 2016 | B2 |
| 9502025 | Kennewick et al. | Nov 2016 | B2 |
| 9508028 | Bannister et al. | Nov 2016 | B2 |
| 9510044 | Pereira et al. | Nov 2016 | B1 |
| 9514470 | Topatan et al. | Dec 2016 | B2 |
| 9516014 | Zafiroglu et al. | Dec 2016 | B2 |
| 9519453 | Perkuhn et al. | Dec 2016 | B2 |
| 9524355 | Forbes et al. | Dec 2016 | B2 |
| 9529500 | Gauci et al. | Dec 2016 | B1 |
| 9531862 | Vadodaria | Dec 2016 | B1 |
| 9535906 | Lee et al. | Jan 2017 | B2 |
| 9536527 | Carlson | Jan 2017 | B1 |
| 9536544 | Osterman et al. | Jan 2017 | B2 |
| 9547647 | Badaskar | Jan 2017 | B2 |
| 9548050 | Gruber et al. | Jan 2017 | B2 |
| 9548979 | Johnson et al. | Jan 2017 | B1 |
| 9569549 | Jenkins et al. | Feb 2017 | B1 |
| 9575964 | Yadgar et al. | Feb 2017 | B2 |
| 9576575 | Heide | Feb 2017 | B2 |
| 9578173 | Sanghavi et al. | Feb 2017 | B2 |
| 9584946 | Lyren et al. | Feb 2017 | B1 |
| 9586318 | Djugash et al. | Mar 2017 | B2 |
| 9602946 | Karkkainen et al. | Mar 2017 | B2 |
| 9607612 | Deleeuw | Mar 2017 | B2 |
| 9612999 | Prakah-Asante et al. | Apr 2017 | B2 |
| 9619200 | Chakladar et al. | Apr 2017 | B2 |
| 9619459 | Hebert et al. | Apr 2017 | B2 |
| 9620113 | Kennewick et al. | Apr 2017 | B2 |
| 9620126 | Chiba | Apr 2017 | B2 |
| 9626695 | Balasubramanian et al. | Apr 2017 | B2 |
| 9626799 | McArdle et al. | Apr 2017 | B2 |
| 9626955 | Fleizach et al. | Apr 2017 | B2 |
| 9633004 | Giuli et al. | Apr 2017 | B2 |
| 9633191 | Fleizach et al. | Apr 2017 | B2 |
| 9633660 | Haughay | Apr 2017 | B2 |
| 9633674 | Sinha | Apr 2017 | B2 |
| 9646313 | Kim et al. | May 2017 | B2 |
| 9648107 | Penilla et al. | May 2017 | B1 |
| 9652453 | Mathur et al. | May 2017 | B2 |
| 9658746 | Cohn et al. | May 2017 | B2 |
| 9659002 | Medlock et al. | May 2017 | B2 |
| 9659298 | Lynch et al. | May 2017 | B2 |
| 9665567 | Li et al. | May 2017 | B2 |
| 9665662 | Gautam et al. | May 2017 | B1 |
| 9668121 | Naik et al. | May 2017 | B2 |
| 9672725 | Dotan-Cohen et al. | Jun 2017 | B2 |
| 9672822 | Brown et al. | Jun 2017 | B2 |
| 9678664 | Zhai et al. | Jun 2017 | B2 |
| 9690542 | Reddy et al. | Jun 2017 | B2 |
| 9691161 | Yalniz et al. | Jun 2017 | B1 |
| 9691378 | Meyers et al. | Jun 2017 | B1 |
| 9696963 | Son et al. | Jul 2017 | B2 |
| 9697016 | Jacob | Jul 2017 | B2 |
| 9697822 | Naik et al. | Jul 2017 | B1 |
| 9697827 | Lilly et al. | Jul 2017 | B1 |
| 9697828 | Prasad et al. | Jul 2017 | B1 |
| 9698999 | Mutagi | Jul 2017 | B2 |
| 9711148 | Sharifi et al. | Jul 2017 | B1 |
| 9720907 | Bangalore et al. | Aug 2017 | B2 |
| 9721566 | Newendorp et al. | Aug 2017 | B2 |
| 9721570 | Beal et al. | Aug 2017 | B1 |
| 9723130 | Rand | Aug 2017 | B2 |
| 9734817 | Putrycz | Aug 2017 | B1 |
| 9734839 | Adams | Aug 2017 | B1 |
| 9741343 | Miles et al. | Aug 2017 | B1 |
| 9747083 | Roman et al. | Aug 2017 | B1 |
| 9747093 | Latino et al. | Aug 2017 | B2 |
| 9755605 | Li et al. | Sep 2017 | B1 |
| 9760566 | Heck et al. | Sep 2017 | B2 |
| 9767710 | Lee et al. | Sep 2017 | B2 |
| 9772994 | Karov et al. | Sep 2017 | B2 |
| 9786271 | Combs et al. | Oct 2017 | B1 |
| 9792907 | Bocklet et al. | Oct 2017 | B2 |
| 9798719 | Karov et al. | Oct 2017 | B2 |
| 9812128 | Mixter et al. | Nov 2017 | B2 |
| 9813882 | Masterman | Nov 2017 | B1 |
| 9818400 | Paulik et al. | Nov 2017 | B2 |
| 9823811 | Brown et al. | Nov 2017 | B2 |
| 9823828 | Zambetti et al. | Nov 2017 | B2 |
| 9824379 | Khandelwal et al. | Nov 2017 | B2 |
| 9824691 | Montero et al. | Nov 2017 | B1 |
| 9824692 | Khoury et al. | Nov 2017 | B1 |
| 9830044 | Brown et al. | Nov 2017 | B2 |
| 9830449 | Wagner | Nov 2017 | B1 |
| 9842168 | Heck et al. | Dec 2017 | B2 |
| 9842584 | Hart et al. | Dec 2017 | B1 |
| 9846685 | Li | Dec 2017 | B2 |
| 9846836 | Gao et al. | Dec 2017 | B2 |
| 9858925 | Gruber et al. | Jan 2018 | B2 |
| 9858927 | Williams et al. | Jan 2018 | B2 |
| 9886953 | Lemay et al. | Feb 2018 | B2 |
| 9887949 | Shepherd et al. | Feb 2018 | B2 |
| 9911415 | Vanblon et al. | Mar 2018 | B2 |
| 9916839 | Scalise et al. | Mar 2018 | B1 |
| 9922642 | Pitschel et al. | Mar 2018 | B2 |
| 9928835 | Tang | Mar 2018 | B1 |
| 9934777 | Joseph et al. | Apr 2018 | B1 |
| 9934785 | Hulaud | Apr 2018 | B1 |
| 9946862 | Yun et al. | Apr 2018 | B2 |
| 9948728 | Linn et al. | Apr 2018 | B2 |
| 9959129 | Kannan et al. | May 2018 | B2 |
| 9959506 | Karppanen | May 2018 | B1 |
| 9966065 | Gruber et al. | May 2018 | B2 |
| 9966068 | Cash et al. | May 2018 | B2 |
| 9967381 | Kashimba et al. | May 2018 | B1 |
| 9971495 | Shetty et al. | May 2018 | B2 |
| 9984686 | Mutagi et al. | May 2018 | B1 |
| 9986419 | Naik et al. | May 2018 | B2 |
| 9990129 | Yang et al. | Jun 2018 | B2 |
| 9990176 | Gray | Jun 2018 | B1 |
| 9990921 | Vanblon et al. | Jun 2018 | B2 |
| 9990926 | Pearce | Jun 2018 | B1 |
| 9996626 | Bailey et al. | Jun 2018 | B1 |
| 9998552 | Ledet | Jun 2018 | B1 |
| 10001817 | Zambetti et al. | Jun 2018 | B2 |
| 10013416 | Bhardwaj et al. | Jul 2018 | B1 |
| 10013654 | Levy et al. | Jul 2018 | B1 |
| 10013979 | Roma et al. | Jul 2018 | B1 |
| 10019436 | Huang | Jul 2018 | B2 |
| 10025378 | Venable et al. | Jul 2018 | B2 |
| 10026209 | Dagley et al. | Jul 2018 | B1 |
| 10027662 | Mutagi et al. | Jul 2018 | B1 |
| 10032451 | Mamkina et al. | Jul 2018 | B1 |
| 10032455 | Newman et al. | Jul 2018 | B2 |
| 10037758 | Jing et al. | Jul 2018 | B2 |
| 10043516 | Saddler et al. | Aug 2018 | B2 |
| 10049161 | Kaneko | Aug 2018 | B2 |
| 10049663 | Orr et al. | Aug 2018 | B2 |
| 10049668 | Huang et al. | Aug 2018 | B2 |
| 10055390 | Sharifi et al. | Aug 2018 | B2 |
| 10055681 | Brown et al. | Aug 2018 | B2 |
| 10068570 | Dai et al. | Sep 2018 | B2 |
| 10074360 | Kim | Sep 2018 | B2 |
| 10074371 | Wang et al. | Sep 2018 | B1 |
| 10078487 | Gruber et al. | Sep 2018 | B2 |
| 10083213 | Podgorny et al. | Sep 2018 | B1 |
| 10083690 | Giuli et al. | Sep 2018 | B2 |
| 10088972 | Brown et al. | Oct 2018 | B2 |
| 10089072 | Piersol et al. | Oct 2018 | B2 |
| 10096319 | Jin et al. | Oct 2018 | B1 |
| 10101887 | Bernstein et al. | Oct 2018 | B2 |
| 10102359 | Cheyer | Oct 2018 | B2 |
| 10115055 | Weiss et al. | Oct 2018 | B2 |
| 10127901 | Zhao et al. | Nov 2018 | B2 |
| 10127908 | Deller et al. | Nov 2018 | B1 |
| 10127926 | James | Nov 2018 | B2 |
| 10134425 | Johnson, Jr. | Nov 2018 | B1 |
| 10135965 | Woolsey et al. | Nov 2018 | B2 |
| 10146923 | Pitkänen et al. | Dec 2018 | B2 |
| 10147421 | Liddell et al. | Dec 2018 | B2 |
| 10147441 | Pogue et al. | Dec 2018 | B1 |
| 10149156 | Tiku et al. | Dec 2018 | B1 |
| 10162817 | Schlesinger et al. | Dec 2018 | B2 |
| 10169329 | Futrell et al. | Jan 2019 | B2 |
| 10170123 | Orr et al. | Jan 2019 | B2 |
| 10170135 | Pearce et al. | Jan 2019 | B1 |
| 10175879 | Missig et al. | Jan 2019 | B2 |
| 10176167 | Evermann | Jan 2019 | B2 |
| 10176802 | Ladhak et al. | Jan 2019 | B1 |
| 10176808 | Lovitt et al. | Jan 2019 | B1 |
| 10178301 | Welbourne et al. | Jan 2019 | B1 |
| 10185542 | Carson et al. | Jan 2019 | B2 |
| 10186254 | Williams et al. | Jan 2019 | B2 |
| 10186266 | Devaraj et al. | Jan 2019 | B1 |
| 10191627 | Cieplinski et al. | Jan 2019 | B2 |
| 10191646 | Zambetti et al. | Jan 2019 | B2 |
| 10191718 | Rhee et al. | Jan 2019 | B2 |
| 10192546 | Piersol et al. | Jan 2019 | B1 |
| 10192552 | Raitio et al. | Jan 2019 | B2 |
| 10192557 | Lee et al. | Jan 2019 | B2 |
| 10198877 | Maltsev et al. | Feb 2019 | B1 |
| 10199051 | Binder et al. | Feb 2019 | B2 |
| 10200824 | Gross et al. | Feb 2019 | B2 |
| 10204627 | Nitz et al. | Feb 2019 | B2 |
| 10210860 | Ward et al. | Feb 2019 | B1 |
| 10216351 | Yang | Feb 2019 | B2 |
| 10216832 | Bangalore et al. | Feb 2019 | B2 |
| 10223066 | Martel et al. | Mar 2019 | B2 |
| 10225711 | Parks et al. | Mar 2019 | B2 |
| 10228904 | Raux | Mar 2019 | B2 |
| 10229109 | Cherepanov et al. | Mar 2019 | B1 |
| 10229356 | Liu et al. | Mar 2019 | B1 |
| 10237711 | Linn et al. | Mar 2019 | B2 |
| 10242501 | Pusch et al. | Mar 2019 | B1 |
| 10248308 | Karunamuni et al. | Apr 2019 | B2 |
| 10249300 | Booker et al. | Apr 2019 | B2 |
| 10249305 | Yu | Apr 2019 | B2 |
| 10255922 | Sharifi et al. | Apr 2019 | B1 |
| 10261672 | Dolbakian et al. | Apr 2019 | B1 |
| 10261830 | Gupta et al. | Apr 2019 | B2 |
| 10269345 | Castillo Sanchez et al. | Apr 2019 | B2 |
| 10275513 | Cowan et al. | Apr 2019 | B1 |
| 10282737 | Clark et al. | May 2019 | B2 |
| 10289205 | Sumter et al. | May 2019 | B1 |
| 10296160 | Shah et al. | May 2019 | B2 |
| 10297253 | Walker, II et al. | May 2019 | B2 |
| 10303772 | Hosn et al. | May 2019 | B2 |
| 10304463 | Mixter et al. | May 2019 | B2 |
| 10311482 | Baldwin | Jun 2019 | B2 |
| 10311871 | Newendorp et al. | Jun 2019 | B2 |
| 10325598 | Basye et al. | Jun 2019 | B2 |
| 10332509 | Catanzaro et al. | Jun 2019 | B2 |
| 10332513 | D'souza et al. | Jun 2019 | B1 |
| 10332518 | Garg et al. | Jun 2019 | B2 |
| 10339224 | Fukuoka | Jul 2019 | B2 |
| 10339714 | Corso et al. | Jul 2019 | B2 |
| 10339925 | Rastrow et al. | Jul 2019 | B1 |
| 10346540 | Karov et al. | Jul 2019 | B2 |
| 10346541 | Phillips et al. | Jul 2019 | B1 |
| 10346753 | Soon-Shiong et al. | Jul 2019 | B2 |
| 10346878 | Ostermann et al. | Jul 2019 | B1 |
| 10353975 | Oh et al. | Jul 2019 | B2 |
| 10354168 | Bluche | Jul 2019 | B2 |
| 10354677 | Mohamed et al. | Jul 2019 | B2 |
| 10356243 | Sanghavi et al. | Jul 2019 | B2 |
| 10360305 | Larcheveque et al. | Jul 2019 | B2 |
| 10360716 | Van Der Meulen et al. | Jul 2019 | B1 |
| 10365887 | Mulherkar | Jul 2019 | B1 |
| 10366160 | Castelli et al. | Jul 2019 | B2 |
| 10366692 | Adams et al. | Jul 2019 | B1 |
| 10372814 | Gliozzo et al. | Aug 2019 | B2 |
| 10372881 | Ingrassia, Jr. et al. | Aug 2019 | B2 |
| 10389876 | Engelke et al. | Aug 2019 | B2 |
| 10402066 | Kawana | Sep 2019 | B2 |
| 10403283 | Schramm et al. | Sep 2019 | B1 |
| 10409454 | Kagan et al. | Sep 2019 | B2 |
| 10410637 | Paulik et al. | Sep 2019 | B2 |
| 10417037 | Gruber et al. | Sep 2019 | B2 |
| 10417344 | Futrell et al. | Sep 2019 | B2 |
| 10417554 | Scheffler | Sep 2019 | B2 |
| 10431210 | Huang et al. | Oct 2019 | B1 |
| 10437928 | Bhaya et al. | Oct 2019 | B2 |
| 10446142 | Lim et al. | Oct 2019 | B2 |
| 10453117 | Reavely et al. | Oct 2019 | B1 |
| 10469665 | Bell et al. | Nov 2019 | B1 |
| 10474961 | Brigham et al. | Nov 2019 | B2 |
| 10475446 | Gruber et al. | Nov 2019 | B2 |
| 10482875 | Henry | Nov 2019 | B2 |
| 10490195 | Krishnamoorthy et al. | Nov 2019 | B1 |
| 10496364 | Yao | Dec 2019 | B2 |
| 10496705 | Irani et al. | Dec 2019 | B1 |
| 10497365 | Gruber et al. | Dec 2019 | B2 |
| 10497366 | Sapugay et al. | Dec 2019 | B2 |
| 10504518 | Irani et al. | Dec 2019 | B1 |
| 10512750 | Lewin et al. | Dec 2019 | B1 |
| 10515133 | Sharifi | Dec 2019 | B1 |
| 10515623 | Grizzel | Dec 2019 | B1 |
| 10521946 | Roche et al. | Dec 2019 | B1 |
| 10528386 | Yu | Jan 2020 | B2 |
| 10540976 | Van Os et al. | Jan 2020 | B2 |
| 10558893 | Bluche | Feb 2020 | B2 |
| 10559225 | Tao et al. | Feb 2020 | B1 |
| 10559299 | Arel et al. | Feb 2020 | B1 |
| 10566007 | Fawaz et al. | Feb 2020 | B2 |
| 10568032 | Freeman et al. | Feb 2020 | B2 |
| 10572885 | Guo et al. | Feb 2020 | B1 |
| 10579401 | Dawes | Mar 2020 | B2 |
| 10580409 | Walker, II et al. | Mar 2020 | B2 |
| 10582355 | Lebeau et al. | Mar 2020 | B1 |
| 10585957 | Heck et al. | Mar 2020 | B2 |
| 10586369 | Roche et al. | Mar 2020 | B1 |
| 10599449 | Chatzipanagiotis et al. | Mar 2020 | B1 |
| 10628483 | Rao et al. | Apr 2020 | B1 |
| 10629186 | Slifka | Apr 2020 | B1 |
| 10630795 | Aoki et al. | Apr 2020 | B2 |
| 10642934 | Heck et al. | May 2020 | B2 |
| 10649652 | Sun | May 2020 | B2 |
| 10659851 | Lister et al. | May 2020 | B2 |
| 10671428 | Zeitlin | Jun 2020 | B2 |
| 10679007 | Jia et al. | Jun 2020 | B2 |
| 10679608 | Mixter et al. | Jun 2020 | B2 |
| 10684099 | Zaetterqvist | Jun 2020 | B2 |
| 10684703 | Hindi et al. | Jun 2020 | B2 |
| 10699697 | Qian et al. | Jun 2020 | B2 |
| 10706841 | Gruber et al. | Jul 2020 | B2 |
| 10721190 | Zhao et al. | Jul 2020 | B2 |
| 10732708 | Roche et al. | Aug 2020 | B1 |
| 10743107 | Yoshioka et al. | Aug 2020 | B1 |
| 10748529 | Milden | Aug 2020 | B1 |
| 10748546 | Kim et al. | Aug 2020 | B2 |
| 10754658 | Tamiya | Aug 2020 | B2 |
| 10755032 | Douglas et al. | Aug 2020 | B2 |
| 10757499 | Vautrin et al. | Aug 2020 | B1 |
| 10769385 | Evermann | Sep 2020 | B2 |
| 10778839 | Newstadt et al. | Sep 2020 | B1 |
| 10783151 | Bushkin et al. | Sep 2020 | B1 |
| 10783883 | Mixter et al. | Sep 2020 | B2 |
| 10789945 | Acero et al. | Sep 2020 | B2 |
| 10791176 | Phipps et al. | Sep 2020 | B2 |
| 10795944 | Brown et al. | Oct 2020 | B2 |
| 10796100 | Bangalore et al. | Oct 2020 | B2 |
| 10803255 | Dubyak et al. | Oct 2020 | B2 |
| 10811013 | Secker-Walker et al. | Oct 2020 | B1 |
| 10818288 | Garcia et al. | Oct 2020 | B2 |
| 10842968 | Kahn et al. | Nov 2020 | B1 |
| 10846618 | Ravi et al. | Nov 2020 | B2 |
| 10847142 | Newendorp et al. | Nov 2020 | B2 |
| 10860629 | Gangadharaiah et al. | Dec 2020 | B1 |
| 10861483 | Feinauer et al. | Dec 2020 | B2 |
| 10877637 | Antos et al. | Dec 2020 | B1 |
| 10880668 | Robinson et al. | Dec 2020 | B1 |
| 10885277 | Ravi et al. | Jan 2021 | B2 |
| 10892996 | Piersol | Jan 2021 | B2 |
| 10909459 | Tsatsin et al. | Feb 2021 | B2 |
| 10942703 | Martel et al. | Mar 2021 | B2 |
| 10944859 | Weinstein et al. | Mar 2021 | B2 |
| 10957311 | Solomon et al. | Mar 2021 | B2 |
| 10957337 | Chen et al. | Mar 2021 | B2 |
| 10970660 | Harris et al. | Apr 2021 | B1 |
| 10974139 | Feder et al. | Apr 2021 | B2 |
| 10978056 | Challa et al. | Apr 2021 | B1 |
| 10978090 | Binder et al. | Apr 2021 | B2 |
| 10983971 | Carvalho et al. | Apr 2021 | B2 |
| 11009970 | Hindi et al. | May 2021 | B2 |
| 11017766 | Chao et al. | May 2021 | B2 |
| 11037565 | Kudurshian et al. | Jun 2021 | B2 |
| 11061543 | Blatz et al. | Jul 2021 | B1 |
| 11072344 | Provost et al. | Jul 2021 | B2 |
| 11076039 | Weinstein et al. | Jul 2021 | B2 |
| 11094311 | Candelore et al. | Aug 2021 | B2 |
| 11113598 | Socher et al. | Sep 2021 | B2 |
| 11132172 | Naik et al. | Sep 2021 | B1 |
| 11169660 | Gupta et al. | Nov 2021 | B2 |
| 11181988 | Bellegarda et al. | Nov 2021 | B1 |
| 11183205 | Ebenezer et al. | Nov 2021 | B1 |
| 11200027 | Aggarwal et al. | Dec 2021 | B2 |
| 11204787 | Radebaugh et al. | Dec 2021 | B2 |
| 11210477 | Srinivasan et al. | Dec 2021 | B2 |
| 11269426 | Jorasch et al. | Mar 2022 | B2 |
| 11283631 | Yan et al. | Mar 2022 | B2 |
| 20050075875 | Shozakai et al. | Apr 2005 | A1 |
| 20100067723 | Bergmann | Mar 2010 | A1 |
| 20100086152 | Rank | Apr 2010 | A1 |
| 20100241418 | Maeda | Sep 2010 | A1 |
| 20100332236 | Tan | Dec 2010 | A1 |
| 20110021213 | Carr | Jan 2011 | A1 |
| 20110295590 | Lloyd et al. | Dec 2011 | A1 |
| 20120002820 | Leichter | Jan 2012 | A1 |
| 20120005224 | Ahrens et al. | Jan 2012 | A1 |
| 20120005602 | Anttila et al. | Jan 2012 | A1 |
| 20120008754 | Mukherjee et al. | Jan 2012 | A1 |
| 20120010886 | Razavilar | Jan 2012 | A1 |
| 20120011138 | Dunning et al. | Jan 2012 | A1 |
| 20120013609 | Reponen et al. | Jan 2012 | A1 |
| 20120015629 | Olsen et al. | Jan 2012 | A1 |
| 20120016658 | Wu et al. | Jan 2012 | A1 |
| 20120016678 | Gruber et al. | Jan 2012 | A1 |
| 20120019400 | Patel et al. | Jan 2012 | A1 |
| 20120020490 | Leichter | Jan 2012 | A1 |
| 20120020503 | Endo et al. | Jan 2012 | A1 |
| 20120022787 | LeBeau et al. | Jan 2012 | A1 |
| 20120022857 | Baldwin et al. | Jan 2012 | A1 |
| 20120022860 | Lloyd et al. | Jan 2012 | A1 |
| 20120022865 | Milstein | Jan 2012 | A1 |
| 20120022868 | LeBeau et al. | Jan 2012 | A1 |
| 20120022869 | Lloyd et al. | Jan 2012 | A1 |
| 20120022870 | Kristjansson et al. | Jan 2012 | A1 |
| 20120022872 | Gruber et al. | Jan 2012 | A1 |
| 20120022874 | Lloyd et al. | Jan 2012 | A1 |
| 20120022876 | LeBeau et al. | Jan 2012 | A1 |
| 20120022967 | Bachman et al. | Jan 2012 | A1 |
| 20120023088 | Cheng et al. | Jan 2012 | A1 |
| 20120023095 | Wadycki et al. | Jan 2012 | A1 |
| 20120023462 | Rosing et al. | Jan 2012 | A1 |
| 20120026395 | Jin et al. | Feb 2012 | A1 |
| 20120029661 | Jones et al. | Feb 2012 | A1 |
| 20120029910 | Medlock et al. | Feb 2012 | A1 |
| 20120034904 | LeBeau et al. | Feb 2012 | A1 |
| 20120035907 | Lebeau et al. | Feb 2012 | A1 |
| 20120035908 | Lebeau et al. | Feb 2012 | A1 |
| 20120035924 | Jitkoff et al. | Feb 2012 | A1 |
| 20120035925 | Friend et al. | Feb 2012 | A1 |
| 20120035926 | Ambler | Feb 2012 | A1 |
| 20120035931 | LeBeau et al. | Feb 2012 | A1 |
| 20120035932 | Jitkoff et al. | Feb 2012 | A1 |
| 20120035935 | Park et al. | Feb 2012 | A1 |
| 20120036556 | LeBeau et al. | Feb 2012 | A1 |
| 20120039539 | Boiman et al. | Feb 2012 | A1 |
| 20120039578 | Issa et al. | Feb 2012 | A1 |
| 20120041752 | Wang et al. | Feb 2012 | A1 |
| 20120041756 | Hanazawa et al. | Feb 2012 | A1 |
| 20120041759 | Barker et al. | Feb 2012 | A1 |
| 20120042014 | Desai et al. | Feb 2012 | A1 |
| 20120042343 | Laligand et al. | Feb 2012 | A1 |
| 20120052945 | Miyamoto et al. | Mar 2012 | A1 |
| 20120053815 | Montanari et al. | Mar 2012 | A1 |
| 20120053829 | Agarwal et al. | Mar 2012 | A1 |
| 20120053945 | Gupta et al. | Mar 2012 | A1 |
| 20120055253 | Sinha | Mar 2012 | A1 |
| 20120056815 | Mehra | Mar 2012 | A1 |
| 20120058783 | Kim et al. | Mar 2012 | A1 |
| 20120059655 | Cartales | Mar 2012 | A1 |
| 20120059813 | Sejnoha et al. | Mar 2012 | A1 |
| 20120060052 | White et al. | Mar 2012 | A1 |
| 20120062473 | Xiao et al. | Mar 2012 | A1 |
| 20120064975 | Gault et al. | Mar 2012 | A1 |
| 20120065972 | Strifler et al. | Mar 2012 | A1 |
| 20120066212 | Jennings | Mar 2012 | A1 |
| 20120066581 | Spalink | Mar 2012 | A1 |
| 20120075054 | Ge et al. | Mar 2012 | A1 |
| 20120075184 | Madhvanath | Mar 2012 | A1 |
| 20120077479 | Sabotta et al. | Mar 2012 | A1 |
| 20120078611 | Soltani et al. | Mar 2012 | A1 |
| 20120078624 | Yook et al. | Mar 2012 | A1 |
| 20120078627 | Wagner | Mar 2012 | A1 |
| 20120078635 | Rothkopf et al. | Mar 2012 | A1 |
| 20120078747 | Chakrabarti et al. | Mar 2012 | A1 |
| 20120082317 | Pance et al. | Apr 2012 | A1 |
| 20120083286 | Kim et al. | Apr 2012 | A1 |
| 20120084086 | Gilbert et al. | Apr 2012 | A1 |
| 20120084087 | Yang et al. | Apr 2012 | A1 |
| 20120084089 | Lloyd et al. | Apr 2012 | A1 |
| 20120084251 | Lingenfelder et al. | Apr 2012 | A1 |
| 20120084634 | Wong et al. | Apr 2012 | A1 |
| 20120088219 | Briscoe et al. | Apr 2012 | A1 |
| 20120089331 | Schmidt et al. | Apr 2012 | A1 |
| 20120089659 | Halevi et al. | Apr 2012 | A1 |
| 20120094645 | Jeffrey | Apr 2012 | A1 |
| 20120101823 | Weng et al. | Apr 2012 | A1 |
| 20120105257 | Murillo et al. | May 2012 | A1 |
| 20120108166 | Hymel | May 2012 | A1 |
| 20120108221 | Thomas et al. | May 2012 | A1 |
| 20120109632 | Sugiura et al. | May 2012 | A1 |
| 20120109753 | Kennewick et al. | May 2012 | A1 |
| 20120109997 | Sparks et al. | May 2012 | A1 |
| 20120110456 | Larco et al. | May 2012 | A1 |
| 20120114108 | Katis et al. | May 2012 | A1 |
| 20120116770 | Chen et al. | May 2012 | A1 |
| 20120117499 | Mori et al. | May 2012 | A1 |
| 20120117590 | Agnihotri et al. | May 2012 | A1 |
| 20120124126 | Alcazar et al. | May 2012 | A1 |
| 20120124177 | Sparks | May 2012 | A1 |
| 20120124178 | Sparks | May 2012 | A1 |
| 20120128322 | Shaffer et al. | May 2012 | A1 |
| 20120130709 | Bocchieri et al. | May 2012 | A1 |
| 20120130717 | Xu et al. | May 2012 | A1 |
| 20120130978 | Li et al. | May 2012 | A1 |
| 20120130995 | Risvik et al. | May 2012 | A1 |
| 20120135714 | King, II | May 2012 | A1 |
| 20120136529 | Curtis et al. | May 2012 | A1 |
| 20120136572 | Norton | May 2012 | A1 |
| 20120136649 | Freising et al. | May 2012 | A1 |
| 20120136658 | Shrum, Jr. et al. | May 2012 | A1 |
| 20120136855 | Ni et al. | May 2012 | A1 |
| 20120136985 | Popescu et al. | May 2012 | A1 |
| 20120137367 | Dupont et al. | May 2012 | A1 |
| 20120287067 | Ikegami | May 2012 | A1 |
| 20120148077 | Aldaz et al. | Jun 2012 | A1 |
| 20120149342 | Cohen et al. | Jun 2012 | A1 |
| 20120149394 | Singh et al. | Jun 2012 | A1 |
| 20120150532 | Mirowski et al. | Jun 2012 | A1 |
| 20120150544 | McLoughlin et al. | Jun 2012 | A1 |
| 20120150580 | Norton | Jun 2012 | A1 |
| 20120158293 | Burnham | Jun 2012 | A1 |
| 20120158399 | Tremblay et al. | Jun 2012 | A1 |
| 20120158422 | Burnham et al. | Jun 2012 | A1 |
| 20120159380 | Kocienda et al. | Jun 2012 | A1 |
| 20120162540 | Ouchi et al. | Jun 2012 | A1 |
| 20120163710 | Skaff et al. | Jun 2012 | A1 |
| 20120166177 | Beld et al. | Jun 2012 | A1 |
| 20120166196 | Ju et al. | Jun 2012 | A1 |
| 20120166429 | Moore et al. | Jun 2012 | A1 |
| 20120166942 | Ramerth et al. | Jun 2012 | A1 |
| 20120166959 | Hilerio et al. | Jun 2012 | A1 |
| 20120166998 | Cotterill et al. | Jun 2012 | A1 |
| 20120173222 | Wang et al. | Jul 2012 | A1 |
| 20120173244 | Kwak et al. | Jul 2012 | A1 |
| 20120173464 | Tur et al. | Jul 2012 | A1 |
| 20120174121 | Treat et al. | Jul 2012 | A1 |
| 20120176255 | Choi et al. | Jul 2012 | A1 |
| 20120179457 | Newman et al. | Jul 2012 | A1 |
| 20120179467 | Williams et al. | Jul 2012 | A1 |
| 20120179471 | Newman et al. | Jul 2012 | A1 |
| 20120185237 | Gajic et al. | Jul 2012 | A1 |
| 20120185480 | Ni et al. | Jul 2012 | A1 |
| 20120185781 | Guzman et al. | Jul 2012 | A1 |
| 20120185803 | Wang et al. | Jul 2012 | A1 |
| 20120185821 | Yaseen et al. | Jul 2012 | A1 |
| 20120191461 | Lin et al. | Jul 2012 | A1 |
| 20120192096 | Bowman et al. | Jul 2012 | A1 |
| 20120197743 | Grigg et al. | Aug 2012 | A1 |
| 20120197967 | Sivavakeesar | Aug 2012 | A1 |
| 20120197995 | Caruso | Aug 2012 | A1 |
| 20120197998 | Kessel et al. | Aug 2012 | A1 |
| 20120200489 | Miyashita et al. | Aug 2012 | A1 |
| 20120201362 | Crossan et al. | Aug 2012 | A1 |
| 20120203767 | Williams et al. | Aug 2012 | A1 |
| 20120208592 | Davis et al. | Aug 2012 | A1 |
| 20120209454 | Miller et al. | Aug 2012 | A1 |
| 20120209654 | Romagnino et al. | Aug 2012 | A1 |
| 20120209853 | Desai et al. | Aug 2012 | A1 |
| 20120209874 | Wong et al. | Aug 2012 | A1 |
| 20120210266 | Jiang et al. | Aug 2012 | A1 |
| 20120210378 | Mccoy et al. | Aug 2012 | A1 |
| 20120214141 | Raya et al. | Aug 2012 | A1 |
| 20120214517 | Singh et al. | Aug 2012 | A1 |
| 20120215640 | Ramer et al. | Aug 2012 | A1 |
| 20120215762 | Hall et al. | Aug 2012 | A1 |
| 20120221339 | Wang et al. | Aug 2012 | A1 |
| 20120221552 | Reponen et al. | Aug 2012 | A1 |
| 20120222132 | Burger et al. | Aug 2012 | A1 |
| 20120223889 | Medlock et al. | Sep 2012 | A1 |
| 20120223936 | Aughey et al. | Sep 2012 | A1 |
| 20120226491 | Yamazaki et al. | Sep 2012 | A1 |
| 20120232885 | Barbosa et al. | Sep 2012 | A1 |
| 20120232886 | Capuozzo et al. | Sep 2012 | A1 |
| 20120232906 | Lindahl | Sep 2012 | A1 |
| 20120233207 | Mohajer | Sep 2012 | A1 |
| 20120233266 | Hassan et al. | Sep 2012 | A1 |
| 20120233280 | Ebara | Sep 2012 | A1 |
| 20120239403 | Cano et al. | Sep 2012 | A1 |
| 20120239661 | Giblin | Sep 2012 | A1 |
| 20120239761 | Linner et al. | Sep 2012 | A1 |
| 20120242482 | Elumalai et al. | Sep 2012 | A1 |
| 20120245719 | Story, Jr. et al. | Sep 2012 | A1 |
| 20120245924 | Brun | Sep 2012 | A1 |
| 20120245939 | Braho et al. | Sep 2012 | A1 |
| 20120245941 | Cheyer | Sep 2012 | A1 |
| 20120245944 | Gruber et al. | Sep 2012 | A1 |
| 20120246064 | Balkow | Sep 2012 | A1 |
| 20120250858 | Iqbal et al. | Oct 2012 | A1 |
| 20120252367 | Gaglio et al. | Oct 2012 | A1 |
| 20120252540 | Kirigaya | Oct 2012 | A1 |
| 20120253785 | Hamid et al. | Oct 2012 | A1 |
| 20120253791 | Heck et al. | Oct 2012 | A1 |
| 20120254143 | Varma et al. | Oct 2012 | A1 |
| 20120254152 | Park et al. | Oct 2012 | A1 |
| 20120254290 | Naaman | Oct 2012 | A1 |
| 20120259615 | Morin et al. | Oct 2012 | A1 |
| 20120259638 | Kalinli | Oct 2012 | A1 |
| 20120262296 | Bezar | Oct 2012 | A1 |
| 20120265482 | Grokop et al. | Oct 2012 | A1 |
| 20120265528 | Gruber et al. | Oct 2012 | A1 |
| 20120265535 | Bryant-Rich et al. | Oct 2012 | A1 |
| 20120265787 | Hsu et al. | Oct 2012 | A1 |
| 20120265806 | Blanchflower et al. | Oct 2012 | A1 |
| 20120271625 | Bernard | Oct 2012 | A1 |
| 20120271634 | Lenke | Oct 2012 | A1 |
| 20120271635 | Ljolje | Oct 2012 | A1 |
| 20120271640 | Basir | Oct 2012 | A1 |
| 20120271676 | Aravamudan et al. | Oct 2012 | A1 |
| 20120272177 | Vaghefinazari et al. | Oct 2012 | A1 |
| 20120275377 | Lehane et al. | Nov 2012 | A1 |
| 20120278073 | Weider et al. | Nov 2012 | A1 |
| 20120278744 | Kozitsyn et al. | Nov 2012 | A1 |
| 20120278812 | Wang | Nov 2012 | A1 |
| 20120284015 | Drewes | Nov 2012 | A1 |
| 20120284027 | Mallett et al. | Nov 2012 | A1 |
| 20120290291 | Shelley et al. | Nov 2012 | A1 |
| 20120290300 | Lee et al. | Nov 2012 | A1 |
| 20120290657 | Parks et al. | Nov 2012 | A1 |
| 20120290680 | Hwang | Nov 2012 | A1 |
| 20120295708 | Hernandez-Abrego et al. | Nov 2012 | A1 |
| 20120296638 | Patwa | Nov 2012 | A1 |
| 20120296649 | Bansal et al. | Nov 2012 | A1 |
| 20120296654 | Hendrickson et al. | Nov 2012 | A1 |
| 20120296891 | Rangan | Nov 2012 | A1 |
| 20120297341 | Glazer et al. | Nov 2012 | A1 |
| 20120297348 | Santoro | Nov 2012 | A1 |
| 20120303369 | Brush et al. | Nov 2012 | A1 |
| 20120303371 | Labsky et al. | Nov 2012 | A1 |
| 20120304124 | Chen et al. | Nov 2012 | A1 |
| 20120304239 | Shahraray et al. | Nov 2012 | A1 |
| 20120309363 | Gruber et al. | Dec 2012 | A1 |
| 20120310642 | Cao et al. | Dec 2012 | A1 |
| 20120310649 | Cannistraro et al. | Dec 2012 | A1 |
| 20120310652 | O'Sullivan | Dec 2012 | A1 |
| 20120310922 | Johnson et al. | Dec 2012 | A1 |
| 20120311478 | Van Os et al. | Dec 2012 | A1 |
| 20120311583 | Gruber et al. | Dec 2012 | A1 |
| 20120311584 | Gruber et al. | Dec 2012 | A1 |
| 20120311585 | Gruber et al. | Dec 2012 | A1 |
| 20120316774 | Yariv et al. | Dec 2012 | A1 |
| 20120316862 | Sultan et al. | Dec 2012 | A1 |
| 20120316875 | Nyquist et al. | Dec 2012 | A1 |
| 20120316878 | Singleton et al. | Dec 2012 | A1 |
| 20120316955 | Panguluri et al. | Dec 2012 | A1 |
| 20120317194 | Tian | Dec 2012 | A1 |
| 20120317498 | Logan et al. | Dec 2012 | A1 |
| 20120321112 | Schubert et al. | Dec 2012 | A1 |
| 20120323560 | Cortes et al. | Dec 2012 | A1 |
| 20120324391 | Tocci | Dec 2012 | A1 |
| 20120327009 | Fleizach | Dec 2012 | A1 |
| 20120329529 | Van Der Raadt | Dec 2012 | A1 |
| 20120330660 | Jaiswal | Dec 2012 | A1 |
| 20120330661 | Lindahl | Dec 2012 | A1 |
| 20120330990 | Chen et al. | Dec 2012 | A1 |
| 20130002716 | Walker et al. | Jan 2013 | A1 |
| 20130005405 | Prociw | Jan 2013 | A1 |
| 20130006633 | Grokop et al. | Jan 2013 | A1 |
| 20130006637 | Kanevsky et al. | Jan 2013 | A1 |
| 20130006638 | Lindahl | Jan 2013 | A1 |
| 20130007240 | Qiu et al. | Jan 2013 | A1 |
| 20130007648 | Gamon et al. | Jan 2013 | A1 |
| 20130009858 | Lacey | Jan 2013 | A1 |
| 20130010575 | He et al. | Jan 2013 | A1 |
| 20130013313 | Shechtman et al. | Jan 2013 | A1 |
| 20130013319 | Grant et al. | Jan 2013 | A1 |
| 20130014026 | Beringer et al. | Jan 2013 | A1 |
| 20130014143 | Bhatia et al. | Jan 2013 | A1 |
| 20130018659 | Chi | Jan 2013 | A1 |
| 20130018863 | Regan et al. | Jan 2013 | A1 |
| 20130022189 | Ganong et al. | Jan 2013 | A1 |
| 20130024277 | Tuchman et al. | Jan 2013 | A1 |
| 20130024576 | Dishneau et al. | Jan 2013 | A1 |
| 20130027875 | Zhu et al. | Jan 2013 | A1 |
| 20130028404 | Omalley et al. | Jan 2013 | A1 |
| 20130030787 | Cancedda et al. | Jan 2013 | A1 |
| 20130030789 | Dalce | Jan 2013 | A1 |
| 20130030804 | Zavaliagkos et al. | Jan 2013 | A1 |
| 20130030815 | Madhvanath et al. | Jan 2013 | A1 |
| 20130030904 | Aidasani et al. | Jan 2013 | A1 |
| 20130030913 | Zhu et al. | Jan 2013 | A1 |
| 20130030955 | David | Jan 2013 | A1 |
| 20130031162 | Willis et al. | Jan 2013 | A1 |
| 20130031476 | Coin et al. | Jan 2013 | A1 |
| 20130176208 | Tanaka et al. | Jan 2013 | A1 |
| 20130033643 | Kim et al. | Feb 2013 | A1 |
| 20130035086 | Chardon et al. | Feb 2013 | A1 |
| 20130035942 | Kim et al. | Feb 2013 | A1 |
| 20130035961 | Yegnanarayanan | Feb 2013 | A1 |
| 20130035994 | Pattan et al. | Feb 2013 | A1 |
| 20130036200 | Roberts et al. | Feb 2013 | A1 |
| 20130038618 | Urbach | Feb 2013 | A1 |
| 20130041647 | Ramerth et al. | Feb 2013 | A1 |
| 20130041654 | Walker et al. | Feb 2013 | A1 |
| 20130041661 | Lee et al. | Feb 2013 | A1 |
| 20130041665 | Jang et al. | Feb 2013 | A1 |
| 20130041667 | Longe et al. | Feb 2013 | A1 |
| 20130041685 | Yegnanarayanan | Feb 2013 | A1 |
| 20130041968 | Cohen et al. | Feb 2013 | A1 |
| 20130046544 | Kay et al. | Feb 2013 | A1 |
| 20130047178 | Moon et al. | Feb 2013 | A1 |
| 20130050089 | Neels et al. | Feb 2013 | A1 |
| 20130054550 | Bolohan | Feb 2013 | A1 |
| 20130054609 | Rajput et al. | Feb 2013 | A1 |
| 20130054613 | Bishop | Feb 2013 | A1 |
| 20130054631 | Govani et al. | Feb 2013 | A1 |
| 20130054675 | Jenkins et al. | Feb 2013 | A1 |
| 20130054706 | Graham et al. | Feb 2013 | A1 |
| 20130054945 | Free et al. | Feb 2013 | A1 |
| 20130055099 | Yao et al. | Feb 2013 | A1 |
| 20130055147 | Vasudev et al. | Feb 2013 | A1 |
| 20130055201 | No et al. | Feb 2013 | A1 |
| 20130060571 | Soemo et al. | Mar 2013 | A1 |
| 20130060807 | Rambhia et al. | Mar 2013 | A1 |
| 20130061139 | Mahkovec et al. | Mar 2013 | A1 |
| 20130063611 | Papakipos et al. | Mar 2013 | A1 |
| 20130066832 | Sheehan et al. | Mar 2013 | A1 |
| 20130067307 | Tian et al. | Mar 2013 | A1 |
| 20130067312 | Rose | Mar 2013 | A1 |
| 20130067421 | Osman et al. | Mar 2013 | A1 |
| 20130069769 | Pennington et al. | Mar 2013 | A1 |
| 20130073286 | Bastea-Forte et al. | Mar 2013 | A1 |
| 20130073293 | Jang et al. | Mar 2013 | A1 |
| 20130073346 | Chun et al. | Mar 2013 | A1 |
| 20130073580 | Mehanna et al. | Mar 2013 | A1 |
| 20130073676 | Cockcroft | Mar 2013 | A1 |
| 20130078930 | Chen et al. | Mar 2013 | A1 |
| 20130080152 | Brun et al. | Mar 2013 | A1 |
| 20130080162 | Chang et al. | Mar 2013 | A1 |
| 20130080167 | Mozer | Mar 2013 | A1 |
| 20130080177 | Chen | Mar 2013 | A1 |
| 20130080178 | Kang et al. | Mar 2013 | A1 |
| 20130080251 | Dempski | Mar 2013 | A1 |
| 20130080972 | Moshrefi et al. | Mar 2013 | A1 |
| 20130082967 | Hillis et al. | Apr 2013 | A1 |
| 20130084882 | Khorashadi et al. | Apr 2013 | A1 |
| 20130085755 | Bringert et al. | Apr 2013 | A1 |
| 20130085757 | Nakamura et al. | Apr 2013 | A1 |
| 20130085761 | Bringert et al. | Apr 2013 | A1 |
| 20130086609 | Levy et al. | Apr 2013 | A1 |
| 20130090921 | Liu et al. | Apr 2013 | A1 |
| 20130091090 | Spivack et al. | Apr 2013 | A1 |
| 20130095805 | LeBeau et al. | Apr 2013 | A1 |
| 20130096909 | Brun et al. | Apr 2013 | A1 |
| 20130096911 | Beaufort et al. | Apr 2013 | A1 |
| 20130096917 | Edgar et al. | Apr 2013 | A1 |
| 20130097566 | Berglund | Apr 2013 | A1 |
| 20130097682 | Zeljkovic et al. | Apr 2013 | A1 |
| 20130100017 | Papakipos et al. | Apr 2013 | A1 |
| 20130100268 | Mihailidis et al. | Apr 2013 | A1 |
| 20130103383 | Du et al. | Apr 2013 | A1 |
| 20130103391 | Millmore et al. | Apr 2013 | A1 |
| 20130103405 | Namba et al. | Apr 2013 | A1 |
| 20130103698 | Schlipf | Apr 2013 | A1 |
| 20130106742 | Lee et al. | May 2013 | A1 |
| 20130107053 | Ozaki | May 2013 | A1 |
| 20130109412 | Nguyen et al. | May 2013 | A1 |
| 20130110505 | Gruber et al. | May 2013 | A1 |
| 20130110511 | Spiegel et al. | May 2013 | A1 |
| 20130110515 | Guzzoni et al. | May 2013 | A1 |
| 20130110518 | Gruber et al. | May 2013 | A1 |
| 20130110519 | Cheyer et al. | May 2013 | A1 |
| 20130110520 | Cheyer et al. | May 2013 | A1 |
| 20130110943 | Menon et al. | May 2013 | A1 |
| 20130111330 | Staikos et al. | May 2013 | A1 |
| 20130111348 | Gruber et al. | May 2013 | A1 |
| 20130111365 | Chen et al. | May 2013 | A1 |
| 20130111487 | Cheyer et al. | May 2013 | A1 |
| 20130111581 | Griffin et al. | May 2013 | A1 |
| 20130115927 | Gruber et al. | May 2013 | A1 |
| 20130117022 | Chen et al. | May 2013 | A1 |
| 20130124187 | Qin | May 2013 | A1 |
| 20130124189 | Baldwin et al. | May 2013 | A1 |
| 20130124672 | Pan | May 2013 | A1 |
| 20130125168 | Agnihotri et al. | May 2013 | A1 |
| 20130130669 | Xiao et al. | May 2013 | A1 |
| 20130132081 | Ryu et al. | May 2013 | A1 |
| 20130132084 | Stonehocker et al. | May 2013 | A1 |
| 20130132089 | Fanty et al. | May 2013 | A1 |
| 20130132094 | Lim | May 2013 | A1 |
| 20130132871 | Zeng et al. | May 2013 | A1 |
| 20130138440 | Strope et al. | May 2013 | A1 |
| 20130141551 | Kim | Jun 2013 | A1 |
| 20130142317 | Reynolds | Jun 2013 | A1 |
| 20130142345 | Waldmann | Jun 2013 | A1 |
| 20130144594 | Bangalore et al. | Jun 2013 | A1 |
| 20130144616 | Bangalore | Jun 2013 | A1 |
| 20130151258 | Chandrasekar et al. | Jun 2013 | A1 |
| 20130151339 | Kim et al. | Jun 2013 | A1 |
| 20130152092 | Yadgar | Jun 2013 | A1 |
| 20130154811 | Ferren et al. | Jun 2013 | A1 |
| 20130155948 | Pinheiro et al. | Jun 2013 | A1 |
| 20130156198 | Kim et al. | Jun 2013 | A1 |
| 20130157629 | Lee et al. | Jun 2013 | A1 |
| 20130158977 | Senior | Jun 2013 | A1 |
| 20130159847 | Banke et al. | Jun 2013 | A1 |
| 20130159861 | Rottler et al. | Jun 2013 | A1 |
| 20130165232 | Nelson et al. | Jun 2013 | A1 |
| 20130166278 | James et al. | Jun 2013 | A1 |
| 20130166303 | Chang et al. | Jun 2013 | A1 |
| 20130166332 | Hammad | Jun 2013 | A1 |
| 20130166442 | Nakajima et al. | Jun 2013 | A1 |
| 20130167242 | Paliwal | Jun 2013 | A1 |
| 20130170738 | Capuozzo et al. | Jul 2013 | A1 |
| 20130172022 | Seymour et al. | Jul 2013 | A1 |
| 20130173258 | Liu et al. | Jul 2013 | A1 |
| 20130173268 | Weng et al. | Jul 2013 | A1 |
| 20130173513 | Chu et al. | Jul 2013 | A1 |
| 20130173610 | Hu et al. | Jul 2013 | A1 |
| 20130173614 | Ismalon | Jul 2013 | A1 |
| 20130174034 | Brown et al. | Jul 2013 | A1 |
| 20130176147 | Anderson et al. | Jul 2013 | A1 |
| 20130176244 | Yamamoto et al. | Jul 2013 | A1 |
| 20130176592 | Sasaki | Jul 2013 | A1 |
| 20130179168 | Bae et al. | Jul 2013 | A1 |
| 20130179172 | Nakamura et al. | Jul 2013 | A1 |
| 20130179440 | Gordon | Jul 2013 | A1 |
| 20130179806 | Bastide et al. | Jul 2013 | A1 |
| 20130183942 | Novick et al. | Jul 2013 | A1 |
| 20130183944 | Mozer et al. | Jul 2013 | A1 |
| 20130185059 | Riccardi | Jul 2013 | A1 |
| 20130185066 | Tzirkel-Hancock et al. | Jul 2013 | A1 |
| 20130185074 | Gruber et al. | Jul 2013 | A1 |
| 20130185081 | Cheyer et al. | Jul 2013 | A1 |
| 20130185336 | Singh et al. | Jul 2013 | A1 |
| 20130187850 | Schulz et al. | Jul 2013 | A1 |
| 20130187857 | Griffin et al. | Jul 2013 | A1 |
| 20130190021 | Vieri et al. | Jul 2013 | A1 |
| 20130191117 | Atti et al. | Jul 2013 | A1 |
| 20130191408 | Volkert | Jul 2013 | A1 |
| 20130197911 | Wei et al. | Aug 2013 | A1 |
| 20130197914 | Yelvington et al. | Aug 2013 | A1 |
| 20130198159 | Hendry | Aug 2013 | A1 |
| 20130198841 | Poulson | Aug 2013 | A1 |
| 20130204813 | Master et al. | Aug 2013 | A1 |
| 20130204897 | McDougall | Aug 2013 | A1 |
| 20130204967 | Seo et al. | Aug 2013 | A1 |
| 20130207898 | Sullivan et al. | Aug 2013 | A1 |
| 20130210410 | Xu | Aug 2013 | A1 |
| 20130210492 | You et al. | Aug 2013 | A1 |
| 20130212501 | Anderson et al. | Aug 2013 | A1 |
| 20130218553 | Fujii et al. | Aug 2013 | A1 |
| 20130218560 | Hsiao et al. | Aug 2013 | A1 |
| 20130218574 | Falcon et al. | Aug 2013 | A1 |
| 20130218899 | Raghavan et al. | Aug 2013 | A1 |
| 20130219333 | Palwe et al. | Aug 2013 | A1 |
| 20130222249 | Pasquero et al. | Aug 2013 | A1 |
| 20130223279 | Tinnakornsrisuphap et al. | Aug 2013 | A1 |
| 20130225128 | Gomar | Aug 2013 | A1 |
| 20130226580 | Witt-ehsani | Aug 2013 | A1 |
| 20130226935 | Bai et al. | Aug 2013 | A1 |
| 20130226996 | Itagaki et al. | Aug 2013 | A1 |
| 20130231917 | Naik | Sep 2013 | A1 |
| 20130234947 | Kristensson et al. | Sep 2013 | A1 |
| 20130235987 | Arroniz-Escobar | Sep 2013 | A1 |
| 20130238312 | Waibel | Sep 2013 | A1 |
| 20130238326 | Kim et al. | Sep 2013 | A1 |
| 20130238334 | Ma et al. | Sep 2013 | A1 |
| 20130238540 | O'donoghue et al. | Sep 2013 | A1 |
| 20130238647 | Thompson | Sep 2013 | A1 |
| 20130238729 | Holzman et al. | Sep 2013 | A1 |
| 20130244615 | Miller | Sep 2013 | A1 |
| 20130244633 | Jacobs et al. | Sep 2013 | A1 |
| 20130246048 | Nagase et al. | Sep 2013 | A1 |
| 20130246050 | Yu et al. | Sep 2013 | A1 |
| 20130246329 | Pasquero et al. | Sep 2013 | A1 |
| 20130246920 | Fields et al. | Sep 2013 | A1 |
| 20130253911 | Petri et al. | Sep 2013 | A1 |
| 20130253912 | Medlock et al. | Sep 2013 | A1 |
| 20130260739 | Saino | Oct 2013 | A1 |
| 20130262168 | Makanawala et al. | Oct 2013 | A1 |
| 20130268263 | Park et al. | Oct 2013 | A1 |
| 20130268956 | Recco | Oct 2013 | A1 |
| 20130275117 | Winer | Oct 2013 | A1 |
| 20130275136 | Czahor | Oct 2013 | A1 |
| 20130275138 | Gruber et al. | Oct 2013 | A1 |
| 20130275164 | Gruber et al. | Oct 2013 | A1 |
| 20130275199 | Proctor, Jr. et al. | Oct 2013 | A1 |
| 20130275625 | Taivalsaari et al. | Oct 2013 | A1 |
| 20130275875 | Gruber et al. | Oct 2013 | A1 |
| 20130275899 | Schubert et al. | Oct 2013 | A1 |
| 20130279724 | Stafford et al. | Oct 2013 | A1 |
| 20130282709 | Zhu et al. | Oct 2013 | A1 |
| 20130283168 | Brown et al. | Oct 2013 | A1 |
| 20130283199 | Selig et al. | Oct 2013 | A1 |
| 20130283283 | Wang et al. | Oct 2013 | A1 |
| 20130285913 | Griffin et al. | Oct 2013 | A1 |
| 20130288722 | Ramanujam et al. | Oct 2013 | A1 |
| 20130289991 | Eshwar et al. | Oct 2013 | A1 |
| 20130289993 | Rao | Oct 2013 | A1 |
| 20130289994 | Newman et al. | Oct 2013 | A1 |
| 20130290001 | Yun et al. | Oct 2013 | A1 |
| 20130290222 | Gordo et al. | Oct 2013 | A1 |
| 20130290905 | Luvogt et al. | Oct 2013 | A1 |
| 20130291015 | Pan | Oct 2013 | A1 |
| 20130297078 | Kolavennu | Nov 2013 | A1 |
| 20130297198 | Velde et al. | Nov 2013 | A1 |
| 20130297317 | Lee et al. | Nov 2013 | A1 |
| 20130297319 | Kim | Nov 2013 | A1 |
| 20130297348 | Cardoza et al. | Nov 2013 | A1 |
| 20130298139 | Resnick et al. | Nov 2013 | A1 |
| 20130300645 | Fedorov | Nov 2013 | A1 |
| 20130300648 | Kim et al. | Nov 2013 | A1 |
| 20130303106 | Martin | Nov 2013 | A1 |
| 20130304476 | Kim et al. | Nov 2013 | A1 |
| 20130304479 | Teller et al. | Nov 2013 | A1 |
| 20130304758 | Gruber et al. | Nov 2013 | A1 |
| 20130304815 | Puente et al. | Nov 2013 | A1 |
| 20130305119 | Kern et al. | Nov 2013 | A1 |
| 20130307855 | Lamb et al. | Nov 2013 | A1 |
| 20130307997 | O'Keefe et al. | Nov 2013 | A1 |
| 20130308922 | Sano et al. | Nov 2013 | A1 |
| 20130311179 | Wagner | Nov 2013 | A1 |
| 20130311184 | Badavne et al. | Nov 2013 | A1 |
| 20130311487 | Moore et al. | Nov 2013 | A1 |
| 20130311997 | Gruber et al. | Nov 2013 | A1 |
| 20130315038 | Ferren et al. | Nov 2013 | A1 |
| 20130316679 | Miller et al. | Nov 2013 | A1 |
| 20130316746 | Miller et al. | Nov 2013 | A1 |
| 20130317921 | Havas | Nov 2013 | A1 |
| 20130318478 | Ogura | Nov 2013 | A1 |
| 20130321267 | Bhatti et al. | Dec 2013 | A1 |
| 20130322634 | Bennett et al. | Dec 2013 | A1 |
| 20130322665 | Bennett et al. | Dec 2013 | A1 |
| 20130325340 | Forstall et al. | Dec 2013 | A1 |
| 20130325436 | Wang et al. | Dec 2013 | A1 |
| 20130325443 | Begeja et al. | Dec 2013 | A1 |
| 20130325447 | Levien et al. | Dec 2013 | A1 |
| 20130325448 | Levien et al. | Dec 2013 | A1 |
| 20130325460 | Kim et al. | Dec 2013 | A1 |
| 20130325473 | Larcher et al. | Dec 2013 | A1 |
| 20130325480 | Lee et al. | Dec 2013 | A1 |
| 20130325481 | Van Os et al. | Dec 2013 | A1 |
| 20130325484 | Chakladar et al. | Dec 2013 | A1 |
| 20130325844 | Plaisant | Dec 2013 | A1 |
| 20130325967 | Parks et al. | Dec 2013 | A1 |
| 20130325970 | Roberts et al. | Dec 2013 | A1 |
| 20130325979 | Mansfield et al. | Dec 2013 | A1 |
| 20130326576 | Zhang et al. | Dec 2013 | A1 |
| 20130328809 | Smith | Dec 2013 | A1 |
| 20130329023 | Suplee, III et al. | Dec 2013 | A1 |
| 20130331127 | Sabatelli et al. | Dec 2013 | A1 |
| 20130332113 | Piemonte et al. | Dec 2013 | A1 |
| 20130332159 | Federighi et al. | Dec 2013 | A1 |
| 20130332162 | Keen | Dec 2013 | A1 |
| 20130332164 | Nalk | Dec 2013 | A1 |
| 20130332168 | Kim et al. | Dec 2013 | A1 |
| 20130332172 | Prakash et al. | Dec 2013 | A1 |
| 20130332400 | González | Dec 2013 | A1 |
| 20130332538 | Clark et al. | Dec 2013 | A1 |
| 20130332721 | Chaudhri et al. | Dec 2013 | A1 |
| 20130339028 | Rosner et al. | Dec 2013 | A1 |
| 20130339256 | Shroff | Dec 2013 | A1 |
| 20130339454 | Walker et al. | Dec 2013 | A1 |
| 20130339991 | Ricci | Dec 2013 | A1 |
| 20130342487 | Jeon | Dec 2013 | A1 |
| 20130342672 | Gray et al. | Dec 2013 | A1 |
| 20130343584 | Bennett et al. | Dec 2013 | A1 |
| 20130343721 | Abecassis | Dec 2013 | A1 |
| 20130346016 | Suzuki et al. | Dec 2013 | A1 |
| 20130346065 | Davidson et al. | Dec 2013 | A1 |
| 20130346068 | Solem et al. | Dec 2013 | A1 |
| 20130346347 | Patterson et al. | Dec 2013 | A1 |
| 20130346488 | Lunt et al. | Dec 2013 | A1 |
| 20130347018 | Limp et al. | Dec 2013 | A1 |
| 20130347029 | Tang et al. | Dec 2013 | A1 |
| 20130347102 | Shi | Dec 2013 | A1 |
| 20130347117 | Parks et al. | Dec 2013 | A1 |
| 20140001255 | Anthoine | Jan 2014 | A1 |
| 20140002338 | Raffa et al. | Jan 2014 | A1 |
| 20140006012 | Zhou et al. | Jan 2014 | A1 |
| 20140006025 | Krishnan et al. | Jan 2014 | A1 |
| 20140006027 | Kim et al. | Jan 2014 | A1 |
| 20140006028 | Hu | Jan 2014 | A1 |
| 20140006030 | Fleizach et al. | Jan 2014 | A1 |
| 20140006153 | Thangam et al. | Jan 2014 | A1 |
| 20140006191 | Shankar et al. | Jan 2014 | A1 |
| 20140006483 | Garmark et al. | Jan 2014 | A1 |
| 20140006496 | Dearman et al. | Jan 2014 | A1 |
| 20140006562 | Handa et al. | Jan 2014 | A1 |
| 20140006947 | Garmark et al. | Jan 2014 | A1 |
| 20140006951 | Hunter | Jan 2014 | A1 |
| 20140006955 | Greenzeiger et al. | Jan 2014 | A1 |
| 20140008163 | Mikonaho et al. | Jan 2014 | A1 |
| 20140012574 | Pasupalak et al. | Jan 2014 | A1 |
| 20140012575 | Ganong et al. | Jan 2014 | A1 |
| 20140012580 | Ganong, III et al. | Jan 2014 | A1 |
| 20140012586 | Rubin et al. | Jan 2014 | A1 |
| 20140012587 | Park | Jan 2014 | A1 |
| 20140013336 | Yang | Jan 2014 | A1 |
| 20140019116 | Lundberg et al. | Jan 2014 | A1 |
| 20140019133 | Bao et al. | Jan 2014 | A1 |
| 20140019460 | Sambrani et al. | Jan 2014 | A1 |
| 20140026037 | Garb et al. | Jan 2014 | A1 |
| 20140028029 | Jochman | Jan 2014 | A1 |
| 20140028477 | Michalske | Jan 2014 | A1 |
| 20140028603 | Xie et al. | Jan 2014 | A1 |
| 20140028735 | Williams et al. | Jan 2014 | A1 |
| 20140032453 | Eustice et al. | Jan 2014 | A1 |
| 20140032678 | Koukoumidis et al. | Jan 2014 | A1 |
| 20140033071 | Gruber et al. | Jan 2014 | A1 |
| 20140035823 | Khoe et al. | Feb 2014 | A1 |
| 20140037075 | Bouzid et al. | Feb 2014 | A1 |
| 20140039888 | Taubman et al. | Feb 2014 | A1 |
| 20140039893 | Weiner et al. | Feb 2014 | A1 |
| 20140039894 | Shostak | Feb 2014 | A1 |
| 20140040274 | Aravamudan et al. | Feb 2014 | A1 |
| 20140040748 | Lemay et al. | Feb 2014 | A1 |
| 20140040754 | Donelli | Feb 2014 | A1 |
| 20140040801 | Patel et al. | Feb 2014 | A1 |
| 20140040905 | Tsunoda et al. | Feb 2014 | A1 |
| 20140040918 | Li | Feb 2014 | A1 |
| 20140040961 | Green et al. | Feb 2014 | A1 |
| 20140046934 | Zhou et al. | Feb 2014 | A1 |
| 20140047001 | Phillips et al. | Feb 2014 | A1 |
| 20140051399 | Walker | Feb 2014 | A1 |
| 20140052451 | Cheong et al. | Feb 2014 | A1 |
| 20140052680 | Nitz et al. | Feb 2014 | A1 |
| 20140052791 | Chakra et al. | Feb 2014 | A1 |
| 20140053082 | Park | Feb 2014 | A1 |
| 20140053101 | Buehler et al. | Feb 2014 | A1 |
| 20140053210 | Cheong et al. | Feb 2014 | A1 |
| 20140057610 | Olincy et al. | Feb 2014 | A1 |
| 20140059030 | Hakkani-Tur et al. | Feb 2014 | A1 |
| 20140059423 | Gorga et al. | Feb 2014 | A1 |
| 20140067361 | Nikoulina et al. | Mar 2014 | A1 |
| 20140067371 | Liensberger | Mar 2014 | A1 |
| 20140067402 | Kim | Mar 2014 | A1 |
| 20140067738 | Kingsbury | Mar 2014 | A1 |
| 20140067740 | Solari | Mar 2014 | A1 |
| 20140068751 | Last | Mar 2014 | A1 |
| 20140071241 | Yang et al. | Mar 2014 | A1 |
| 20140074454 | Brown et al. | Mar 2014 | A1 |
| 20140074466 | Sharifi et al. | Mar 2014 | A1 |
| 20140074470 | Jansche et al. | Mar 2014 | A1 |
| 20140074472 | Lin et al. | Mar 2014 | A1 |
| 20140074482 | Ohno | Mar 2014 | A1 |
| 20140074483 | Van Os | Mar 2014 | A1 |
| 20140074589 | Nielsen et al. | Mar 2014 | A1 |
| 20140074815 | Plimton | Mar 2014 | A1 |
| 20140074846 | Moss et al. | Mar 2014 | A1 |
| 20140075453 | Bellessort et al. | Mar 2014 | A1 |
| 20140078065 | Akkok | Mar 2014 | A1 |
| 20140079195 | Srivastava et al. | Mar 2014 | A1 |
| 20140080410 | Jung et al. | Mar 2014 | A1 |
| 20140080428 | Rhoads et al. | Mar 2014 | A1 |
| 20140081619 | Solntseva et al. | Mar 2014 | A1 |
| 20140081633 | Badaskar | Mar 2014 | A1 |
| 20140081635 | Yanagihara | Mar 2014 | A1 |
| 20140081829 | Milne | Mar 2014 | A1 |
| 20140081941 | Bai et al. | Mar 2014 | A1 |
| 20140082500 | Wilensky et al. | Mar 2014 | A1 |
| 20140082501 | Bae et al. | Mar 2014 | A1 |
| 20140082545 | Zhai et al. | Mar 2014 | A1 |
| 20140082715 | Grajek et al. | Mar 2014 | A1 |
| 20140086458 | Rogers | Mar 2014 | A1 |
| 20140087711 | Geyer et al. | Mar 2014 | A1 |
| 20140088952 | Fife et al. | Mar 2014 | A1 |
| 20140088961 | Woodward et al. | Mar 2014 | A1 |
| 20140088964 | Bellegarda | Mar 2014 | A1 |
| 20140088970 | Kang | Mar 2014 | A1 |
| 20140092007 | Kim et al. | Apr 2014 | A1 |
| 20140095171 | Lynch et al. | Apr 2014 | A1 |
| 20140095172 | Cabaco et al. | Apr 2014 | A1 |
| 20140095173 | Lynch et al. | Apr 2014 | A1 |
| 20140095432 | Trumbull et al. | Apr 2014 | A1 |
| 20140095601 | Abuelsaad et al. | Apr 2014 | A1 |
| 20140095965 | Li | Apr 2014 | A1 |
| 20140096077 | Jacob et al. | Apr 2014 | A1 |
| 20140096209 | Saraf et al. | Apr 2014 | A1 |
| 20140098247 | Rao et al. | Apr 2014 | A1 |
| 20140100847 | Ishii et al. | Apr 2014 | A1 |
| 20140101127 | Simhon et al. | Apr 2014 | A1 |
| 20140104175 | Ouyang et al. | Apr 2014 | A1 |
| 20140108017 | Mason et al. | Apr 2014 | A1 |
| 20140108357 | Procops et al. | Apr 2014 | A1 |
| 20140108391 | Volkert | Apr 2014 | A1 |
| 20140108792 | Borzycki et al. | Apr 2014 | A1 |
| 20140112556 | Kalinli-akbacak | Apr 2014 | A1 |
| 20140114554 | Lagassey | Apr 2014 | A1 |
| 20140115062 | Liu et al. | Apr 2014 | A1 |
| 20140115114 | Garmark et al. | Apr 2014 | A1 |
| 20140118155 | Bowers et al. | May 2014 | A1 |
| 20140118624 | Jang et al. | May 2014 | A1 |
| 20140120961 | Buck | May 2014 | A1 |
| 20140122057 | Chelba et al. | May 2014 | A1 |
| 20140122059 | Patel et al. | May 2014 | A1 |
| 20140122085 | Piety et al. | May 2014 | A1 |
| 20140122086 | Kapur et al. | May 2014 | A1 |
| 20140122136 | Jayanthi | May 2014 | A1 |
| 20140122153 | Truitt | May 2014 | A1 |
| 20140123022 | Lee et al. | May 2014 | A1 |
| 20140128021 | Walker et al. | May 2014 | A1 |
| 20140129006 | Chen et al. | May 2014 | A1 |
| 20140129226 | Lee et al. | May 2014 | A1 |
| 20140132935 | Kim et al. | May 2014 | A1 |
| 20140134983 | Jung et al. | May 2014 | A1 |
| 20140135036 | Bonanni et al. | May 2014 | A1 |
| 20140136013 | Wolverton et al. | May 2014 | A1 |
| 20140136187 | Wolverton et al. | May 2014 | A1 |
| 20140136195 | Abdossalami et al. | May 2014 | A1 |
| 20140136212 | Kwon et al. | May 2014 | A1 |
| 20140136946 | Matas | May 2014 | A1 |
| 20140136987 | Rodriguez | May 2014 | A1 |
| 20140142922 | Liang et al. | May 2014 | A1 |
| 20140142923 | Jones et al. | May 2014 | A1 |
| 20140142934 | Kim | May 2014 | A1 |
| 20140142935 | Lindahl et al. | May 2014 | A1 |
| 20140142953 | Kim et al. | May 2014 | A1 |
| 20140143550 | Ganong, III et al. | May 2014 | A1 |
| 20140143721 | Suzuki et al. | May 2014 | A1 |
| 20140143784 | Mistry et al. | May 2014 | A1 |
| 20140146200 | Scott et al. | May 2014 | A1 |
| 20140148209 | Weng et al. | May 2014 | A1 |
| 20140149118 | Lee et al. | May 2014 | A1 |
| 20140152577 | Yuen et al. | Jun 2014 | A1 |
| 20140153709 | Byrd et al. | Jun 2014 | A1 |
| 20140155031 | Lee et al. | Jun 2014 | A1 |
| 20140156262 | Yuen et al. | Jun 2014 | A1 |
| 20140156269 | Lee et al. | Jun 2014 | A1 |
| 20140156279 | Okamoto et al. | Jun 2014 | A1 |
| 20140156564 | Knight et al. | Jun 2014 | A1 |
| 20140157319 | Kimura et al. | Jun 2014 | A1 |
| 20140157422 | Livshits et al. | Jun 2014 | A1 |
| 20140163751 | Davis et al. | Jun 2014 | A1 |
| 20140163951 | Nikoulina et al. | Jun 2014 | A1 |
| 20140163953 | Parikh | Jun 2014 | A1 |
| 20140163954 | Joshi et al. | Jun 2014 | A1 |
| 20140163962 | Castelli et al. | Jun 2014 | A1 |
| 20140163976 | Park et al. | Jun 2014 | A1 |
| 20140163977 | Hoffmeister et al. | Jun 2014 | A1 |
| 20140163978 | Basye et al. | Jun 2014 | A1 |
| 20140163981 | Cook et al. | Jun 2014 | A1 |
| 20140163995 | Burns et al. | Jun 2014 | A1 |
| 20140164305 | Lynch et al. | Jun 2014 | A1 |
| 20140164312 | Lynch et al. | Jun 2014 | A1 |
| 20140164476 | Thomson | Jun 2014 | A1 |
| 20140164508 | Lynch et al. | Jun 2014 | A1 |
| 20140164532 | Lynch et al. | Jun 2014 | A1 |
| 20140164533 | Lynch et al. | Jun 2014 | A1 |
| 20140164953 | Lynch et al. | Jun 2014 | A1 |
| 20140169795 | Clough | Jun 2014 | A1 |
| 20140171064 | Das | Jun 2014 | A1 |
| 20140172412 | Viegas et al. | Jun 2014 | A1 |
| 20140172878 | Clark et al. | Jun 2014 | A1 |
| 20140173445 | Grassiotto | Jun 2014 | A1 |
| 20140173460 | Kim | Jun 2014 | A1 |
| 20140176814 | Ahn | Jun 2014 | A1 |
| 20140179295 | Luebbers et al. | Jun 2014 | A1 |
| 20140180499 | Cooper et al. | Jun 2014 | A1 |
| 20140180689 | Kim | Jun 2014 | A1 |
| 20140180697 | Torok et al. | Jun 2014 | A1 |
| 20140181123 | Tuffet Blaise et al. | Jun 2014 | A1 |
| 20140181741 | Apacible et al. | Jun 2014 | A1 |
| 20140181865 | Koganei | Jun 2014 | A1 |
| 20140188335 | Madhok et al. | Jul 2014 | A1 |
| 20140188460 | Ouyang et al. | Jul 2014 | A1 |
| 20140188477 | Zhang | Jul 2014 | A1 |
| 20140188478 | Zhang | Jul 2014 | A1 |
| 20140188485 | Kim et al. | Jul 2014 | A1 |
| 20140188835 | Zhang et al. | Jul 2014 | A1 |
| 20140195226 | Yun et al. | Jul 2014 | A1 |
| 20140195230 | Han et al. | Jul 2014 | A1 |
| 20140195233 | Bapat et al. | Jul 2014 | A1 |
| 20140195244 | Cha et al. | Jul 2014 | A1 |
| 20140195251 | Zeinstra et al. | Jul 2014 | A1 |
| 20140195252 | Gruber et al. | Jul 2014 | A1 |
| 20140198048 | Unruh et al. | Jul 2014 | A1 |
| 20140200891 | Larcheveque et al. | Jul 2014 | A1 |
| 20140203939 | Harrington et al. | Jul 2014 | A1 |
| 20140205076 | Kumar et al. | Jul 2014 | A1 |
| 20140207439 | Venkatapathy et al. | Jul 2014 | A1 |
| 20140207446 | Klein et al. | Jul 2014 | A1 |
| 20140207447 | Jiang et al. | Jul 2014 | A1 |
| 20140207466 | Smadi | Jul 2014 | A1 |
| 20140207468 | Bartnik | Jul 2014 | A1 |
| 20140207582 | Flinn et al. | Jul 2014 | A1 |
| 20140211944 | Hayward et al. | Jul 2014 | A1 |
| 20140214429 | Pantel | Jul 2014 | A1 |
| 20140214537 | Yoo et al. | Jul 2014 | A1 |
| 20140215367 | Kim et al. | Jul 2014 | A1 |
| 20140215513 | Ramer et al. | Jul 2014 | A1 |
| 20140218372 | Missig et al. | Aug 2014 | A1 |
| 20140222422 | Sarikaya et al. | Aug 2014 | A1 |
| 20140222435 | Li et al. | Aug 2014 | A1 |
| 20140222436 | Binder et al. | Aug 2014 | A1 |
| 20140222678 | Sheets et al. | Aug 2014 | A1 |
| 20140222967 | Harrang et al. | Aug 2014 | A1 |
| 20140223377 | Shaw et al. | Aug 2014 | A1 |
| 20140223481 | Fundament | Aug 2014 | A1 |
| 20140226503 | Cooper et al. | Aug 2014 | A1 |
| 20140229158 | Zweig et al. | Aug 2014 | A1 |
| 20140229184 | Shires | Aug 2014 | A1 |
| 20140230055 | Boehl | Aug 2014 | A1 |
| 20140232570 | Skinder et al. | Aug 2014 | A1 |
| 20140232656 | Pasquero et al. | Aug 2014 | A1 |
| 20140236595 | Gray | Aug 2014 | A1 |
| 20140236986 | Guzman | Aug 2014 | A1 |
| 20140237042 | Ahmed et al. | Aug 2014 | A1 |
| 20140237366 | Poulos et al. | Aug 2014 | A1 |
| 20140244248 | Arisoy et al. | Aug 2014 | A1 |
| 20140244249 | Mohamed et al. | Aug 2014 | A1 |
| 20140244254 | Ju et al. | Aug 2014 | A1 |
| 20140244257 | Colibro et al. | Aug 2014 | A1 |
| 20140244258 | Song et al. | Aug 2014 | A1 |
| 20140244263 | Pontual et al. | Aug 2014 | A1 |
| 20140244266 | Brown et al. | Aug 2014 | A1 |
| 20140244268 | Abdelsamie et al. | Aug 2014 | A1 |
| 20140244270 | Han et al. | Aug 2014 | A1 |
| 20140244271 | Lindahl | Aug 2014 | A1 |
| 20140244712 | Walters et al. | Aug 2014 | A1 |
| 20140245140 | Brown et al. | Aug 2014 | A1 |
| 20140247383 | Dave et al. | Sep 2014 | A1 |
| 20140247926 | Gainsboro et al. | Sep 2014 | A1 |
| 20140249812 | Bou-Ghazale et al. | Sep 2014 | A1 |
| 20140249816 | Pickering et al. | Sep 2014 | A1 |
| 20140249817 | Hart et al. | Sep 2014 | A1 |
| 20140249820 | Hsu et al. | Sep 2014 | A1 |
| 20140249821 | Kennewick et al. | Sep 2014 | A1 |
| 20140250046 | Winn et al. | Sep 2014 | A1 |
| 20140253455 | Mauro et al. | Sep 2014 | A1 |
| 20140257809 | Goel et al. | Sep 2014 | A1 |
| 20140257815 | Zhao et al. | Sep 2014 | A1 |
| 20140257902 | Moore et al. | Sep 2014 | A1 |
| 20140258324 | Mauro et al. | Sep 2014 | A1 |
| 20140258357 | Singh et al. | Sep 2014 | A1 |
| 20140258857 | Dykstra-Erickson et al. | Sep 2014 | A1 |
| 20140258905 | Lee et al. | Sep 2014 | A1 |
| 20140267022 | Kim | Sep 2014 | A1 |
| 20140267599 | Drouin et al. | Sep 2014 | A1 |
| 20140267933 | Young | Sep 2014 | A1 |
| 20140272821 | Pitschel et al. | Sep 2014 | A1 |
| 20140273979 | Van Os et al. | Sep 2014 | A1 |
| 20140274005 | Luna et al. | Sep 2014 | A1 |
| 20140274203 | Ganong, III et al. | Sep 2014 | A1 |
| 20140274211 | Sejnoha et al. | Sep 2014 | A1 |
| 20140278051 | Mcgavran et al. | Sep 2014 | A1 |
| 20140278343 | Tran | Sep 2014 | A1 |
| 20140278349 | Grieves et al. | Sep 2014 | A1 |
| 20140278379 | Coccaro et al. | Sep 2014 | A1 |
| 20140278390 | Kingsbury et al. | Sep 2014 | A1 |
| 20140278391 | Braho et al. | Sep 2014 | A1 |
| 20140278394 | Bastyr et al. | Sep 2014 | A1 |
| 20140278406 | Tsumura et al. | Sep 2014 | A1 |
| 20140278413 | Pitschel et al. | Sep 2014 | A1 |
| 20140278426 | Jost et al. | Sep 2014 | A1 |
| 20140278429 | Ganong, III | Sep 2014 | A1 |
| 20140278435 | Ganong, III et al. | Sep 2014 | A1 |
| 20140278436 | Khanna et al. | Sep 2014 | A1 |
| 20140278438 | Hart et al. | Sep 2014 | A1 |
| 20140278443 | Gunn et al. | Sep 2014 | A1 |
| 20140278444 | Larson et al. | Sep 2014 | A1 |
| 20140278513 | Prakash et al. | Sep 2014 | A1 |
| 20140279622 | Lamoureux et al. | Sep 2014 | A1 |
| 20140279739 | Elkington et al. | Sep 2014 | A1 |
| 20140279787 | Cheng et al. | Sep 2014 | A1 |
| 20140280072 | Coleman | Sep 2014 | A1 |
| 20140280107 | Heymans et al. | Sep 2014 | A1 |
| 20140280138 | Li et al. | Sep 2014 | A1 |
| 20140280292 | Skinder | Sep 2014 | A1 |
| 20140280353 | Delaney et al. | Sep 2014 | A1 |
| 20140280450 | Luna | Sep 2014 | A1 |
| 20140280757 | Tran | Sep 2014 | A1 |
| 20140281944 | Winer | Sep 2014 | A1 |
| 20140281983 | Xian et al. | Sep 2014 | A1 |
| 20140281997 | Fleizach et al. | Sep 2014 | A1 |
| 20140282003 | Gruber et al. | Sep 2014 | A1 |
| 20140282007 | Fleizach | Sep 2014 | A1 |
| 20140282045 | Ayanam et al. | Sep 2014 | A1 |
| 20140282178 | Borzello et al. | Sep 2014 | A1 |
| 20140282201 | Pasquero et al. | Sep 2014 | A1 |
| 20140282203 | Pasquero et al. | Sep 2014 | A1 |
| 20140282559 | Verduzco et al. | Sep 2014 | A1 |
| 20140282586 | Shear et al. | Sep 2014 | A1 |
| 20140282743 | Howard et al. | Sep 2014 | A1 |
| 20140288990 | Moore et al. | Sep 2014 | A1 |
| 20140289508 | Wang | Sep 2014 | A1 |
| 20140297267 | Spencer et al. | Oct 2014 | A1 |
| 20140297281 | Togawa et al. | Oct 2014 | A1 |
| 20140297284 | Gruber et al. | Oct 2014 | A1 |
| 20140297288 | Yu et al. | Oct 2014 | A1 |
| 20140298395 | Yang et al. | Oct 2014 | A1 |
| 20140304086 | Dasdan et al. | Oct 2014 | A1 |
| 20140304605 | Ohmura et al. | Oct 2014 | A1 |
| 20140309990 | Gandrabur et al. | Oct 2014 | A1 |
| 20140309996 | Zhang | Oct 2014 | A1 |
| 20140310001 | Kalns et al. | Oct 2014 | A1 |
| 20140310002 | Nitz et al. | Oct 2014 | A1 |
| 20140310348 | Keskitalo et al. | Oct 2014 | A1 |
| 20140310365 | Sample et al. | Oct 2014 | A1 |
| 20140310595 | Acharya et al. | Oct 2014 | A1 |
| 20140313007 | Harding | Oct 2014 | A1 |
| 20140315492 | Woods | Oct 2014 | A1 |
| 20140316585 | Boesveld et al. | Oct 2014 | A1 |
| 20140317030 | Shen et al. | Oct 2014 | A1 |
| 20140317502 | Brown et al. | Oct 2014 | A1 |
| 20140324429 | Weilhammer et al. | Oct 2014 | A1 |
| 20140324884 | Lindahl et al. | Oct 2014 | A1 |
| 20140330560 | Venkatesha et al. | Nov 2014 | A1 |
| 20140330569 | Kolavennu et al. | Nov 2014 | A1 |
| 20140330951 | Sukoff et al. | Nov 2014 | A1 |
| 20140335823 | Heredia et al. | Nov 2014 | A1 |
| 20140337037 | Chi | Nov 2014 | A1 |
| 20140337048 | Brown et al. | Nov 2014 | A1 |
| 20140337266 | Wolverton et al. | Nov 2014 | A1 |
| 20140337370 | Aravamudan et al. | Nov 2014 | A1 |
| 20140337371 | Li | Nov 2014 | A1 |
| 20140337438 | Govande et al. | Nov 2014 | A1 |
| 20140337621 | Nakhimov | Nov 2014 | A1 |
| 20140337751 | Lim et al. | Nov 2014 | A1 |
| 20140337814 | Kalns et al. | Nov 2014 | A1 |
| 20140342762 | Hajdu et al. | Nov 2014 | A1 |
| 20140343834 | Demerchant et al. | Nov 2014 | A1 |
| 20140343943 | Al-telmissani | Nov 2014 | A1 |
| 20140343946 | Torok et al. | Nov 2014 | A1 |
| 20140344205 | Luna et al. | Nov 2014 | A1 |
| 20140344627 | Schaub et al. | Nov 2014 | A1 |
| 20140344687 | Durham et al. | Nov 2014 | A1 |
| 20140347181 | Luna et al. | Nov 2014 | A1 |
| 20140350847 | Ichinokawa | Nov 2014 | A1 |
| 20140350924 | Zurek et al. | Nov 2014 | A1 |
| 20140350933 | Bak et al. | Nov 2014 | A1 |
| 20140351741 | Medlock et al. | Nov 2014 | A1 |
| 20140351760 | Skory et al. | Nov 2014 | A1 |
| 20140358519 | Mirkin et al. | Dec 2014 | A1 |
| 20140358521 | Mikutel et al. | Dec 2014 | A1 |
| 20140358523 | Sheth et al. | Dec 2014 | A1 |
| 20140358549 | O'Connor et al. | Dec 2014 | A1 |
| 20140359637 | Yan | Dec 2014 | A1 |
| 20140359709 | Nassar et al. | Dec 2014 | A1 |
| 20140361973 | Raux et al. | Dec 2014 | A1 |
| 20140363074 | Dolfing et al. | Dec 2014 | A1 |
| 20140364149 | Marti et al. | Dec 2014 | A1 |
| 20140365209 | Evermann | Dec 2014 | A1 |
| 20140365214 | Bayley | Dec 2014 | A1 |
| 20140365216 | Gruber et al. | Dec 2014 | A1 |
| 20140365226 | Sinha | Dec 2014 | A1 |
| 20140365227 | Cash et al. | Dec 2014 | A1 |
| 20140365407 | Brown et al. | Dec 2014 | A1 |
| 20140365505 | Clark et al. | Dec 2014 | A1 |
| 20140365880 | Bellegarda | Dec 2014 | A1 |
| 20140365885 | Carson et al. | Dec 2014 | A1 |
| 20140365895 | Magahern et al. | Dec 2014 | A1 |
| 20140365922 | Yang | Dec 2014 | A1 |
| 20140365945 | Karunamuni et al. | Dec 2014 | A1 |
| 20140370817 | Luna | Dec 2014 | A1 |
| 20140370841 | Roberts et al. | Dec 2014 | A1 |
| 20140372112 | Xue et al. | Dec 2014 | A1 |
| 20140372356 | Bilal et al. | Dec 2014 | A1 |
| 20140372468 | Collins et al. | Dec 2014 | A1 |
| 20140372931 | Zhai et al. | Dec 2014 | A1 |
| 20140379326 | Sarikaya et al. | Dec 2014 | A1 |
| 20140379334 | Fry | Dec 2014 | A1 |
| 20140379338 | Fry | Dec 2014 | A1 |
| 20140379341 | Seo et al. | Dec 2014 | A1 |
| 20140379798 | Bunner et al. | Dec 2014 | A1 |
| 20140380285 | Gabel et al. | Dec 2014 | A1 |
| 20150003797 | Schmidt | Jan 2015 | A1 |
| 20150004958 | Wang et al. | Jan 2015 | A1 |
| 20150005009 | Tomkins et al. | Jan 2015 | A1 |
| 20150006147 | Schmidt | Jan 2015 | A1 |
| 20150006148 | Goldszmit et al. | Jan 2015 | A1 |
| 20150006157 | Silva et al. | Jan 2015 | A1 |
| 20150006167 | Kato et al. | Jan 2015 | A1 |
| 20150006176 | Pogue et al. | Jan 2015 | A1 |
| 20150006178 | Peng et al. | Jan 2015 | A1 |
| 20150006184 | Marti et al. | Jan 2015 | A1 |
| 20150006199 | Snider et al. | Jan 2015 | A1 |
| 20150012271 | Peng et al. | Jan 2015 | A1 |
| 20150012862 | Ikeda et al. | Jan 2015 | A1 |
| 20150019219 | Tzirkel-Hancock et al. | Jan 2015 | A1 |
| 20150019221 | Lee et al. | Jan 2015 | A1 |
| 20150019445 | Glass et al. | Jan 2015 | A1 |
| 20150019944 | Kalgi | Jan 2015 | A1 |
| 20150019954 | Dalal et al. | Jan 2015 | A1 |
| 20150019974 | Doi et al. | Jan 2015 | A1 |
| 20150025405 | Vairavan et al. | Jan 2015 | A1 |
| 20150025890 | Jagatheesan et al. | Jan 2015 | A1 |
| 20150026620 | Kwon et al. | Jan 2015 | A1 |
| 20150027178 | Scalisi | Jan 2015 | A1 |
| 20150031416 | Labowicz et al. | Jan 2015 | A1 |
| 20150032443 | Karov et al. | Jan 2015 | A1 |
| 20150032457 | Koo et al. | Jan 2015 | A1 |
| 20150033130 | Scheessele | Jan 2015 | A1 |
| 20150033219 | Breiner et al. | Jan 2015 | A1 |
| 20150033275 | Natani et al. | Jan 2015 | A1 |
| 20150034855 | Shen | Feb 2015 | A1 |
| 20150038161 | Jakobson et al. | Feb 2015 | A1 |
| 20150039292 | Suleman et al. | Feb 2015 | A1 |
| 20150039295 | Soschen | Feb 2015 | A1 |
| 20150039299 | Weinstein et al. | Feb 2015 | A1 |
| 20150039305 | Huang | Feb 2015 | A1 |
| 20150039606 | Salaka et al. | Feb 2015 | A1 |
| 20150040012 | Faaborg et al. | Feb 2015 | A1 |
| 20150042640 | Algreatly | Feb 2015 | A1 |
| 20150045003 | Vora et al. | Feb 2015 | A1 |
| 20150045007 | Cash | Feb 2015 | A1 |
| 20150045068 | Soffer et al. | Feb 2015 | A1 |
| 20150046375 | Mandel et al. | Feb 2015 | A1 |
| 20150046434 | Lim et al. | Feb 2015 | A1 |
| 20150046537 | Rakib | Feb 2015 | A1 |
| 20150046828 | Desai et al. | Feb 2015 | A1 |
| 20150050633 | Christmas et al. | Feb 2015 | A1 |
| 20150050923 | Tu et al. | Feb 2015 | A1 |
| 20150051754 | Kwon et al. | Feb 2015 | A1 |
| 20150051901 | Stonehouse et al. | Feb 2015 | A1 |
| 20150053779 | Adamek et al. | Feb 2015 | A1 |
| 20150053781 | Nelson et al. | Feb 2015 | A1 |
| 20150055879 | Yang | Feb 2015 | A1 |
| 20150058013 | Pakhomov et al. | Feb 2015 | A1 |
| 20150058018 | Georges et al. | Feb 2015 | A1 |
| 20150058720 | Smadja et al. | Feb 2015 | A1 |
| 20150058785 | Ookawara | Feb 2015 | A1 |
| 20150065149 | Russell et al. | Mar 2015 | A1 |
| 20150065200 | Namgung et al. | Mar 2015 | A1 |
| 20150066473 | Jeong et al. | Mar 2015 | A1 |
| 20150066479 | Pasupalak et al. | Mar 2015 | A1 |
| 20150066494 | Salvador et al. | Mar 2015 | A1 |
| 20150066496 | Deoras et al. | Mar 2015 | A1 |
| 20150066506 | Romano et al. | Mar 2015 | A1 |
| 20150066516 | Nishikawa et al. | Mar 2015 | A1 |
| 20150066817 | Slayton et al. | Mar 2015 | A1 |
| 20150067485 | Kim et al. | Mar 2015 | A1 |
| 20150067819 | Shribman et al. | Mar 2015 | A1 |
| 20150067822 | Randall | Mar 2015 | A1 |
| 20150071121 | Patil et al. | Mar 2015 | A1 |
| 20150073788 | Sak et al. | Mar 2015 | A1 |
| 20150073804 | Senior et al. | Mar 2015 | A1 |
| 20150074524 | Nicholson et al. | Mar 2015 | A1 |
| 20150074615 | Han et al. | Mar 2015 | A1 |
| 20150081295 | Yun et al. | Mar 2015 | A1 |
| 20150082180 | Ames et al. | Mar 2015 | A1 |
| 20150082229 | Ouyang et al. | Mar 2015 | A1 |
| 20150086174 | Abecassis et al. | Mar 2015 | A1 |
| 20150088511 | Bharadwaj et al. | Mar 2015 | A1 |
| 20150088514 | Typrin | Mar 2015 | A1 |
| 20150088518 | Kim et al. | Mar 2015 | A1 |
| 20150088522 | Hendrickson et al. | Mar 2015 | A1 |
| 20150088523 | Schuster | Mar 2015 | A1 |
| 20150088998 | Isensee et al. | Mar 2015 | A1 |
| 20150092520 | Robison et al. | Apr 2015 | A1 |
| 20150094834 | Vega et al. | Apr 2015 | A1 |
| 20150095031 | Conkie et al. | Apr 2015 | A1 |
| 20150095159 | Kennewick et al. | Apr 2015 | A1 |
| 20150095268 | Greenzeiger et al. | Apr 2015 | A1 |
| 20150095278 | Flinn et al. | Apr 2015 | A1 |
| 20150100144 | Lee et al. | Apr 2015 | A1 |
| 20150100313 | Sharma | Apr 2015 | A1 |
| 20150100316 | Williams et al. | Apr 2015 | A1 |
| 20150100537 | Grieves et al. | Apr 2015 | A1 |
| 20150100983 | Pan | Apr 2015 | A1 |
| 20150106061 | Yang et al. | Apr 2015 | A1 |
| 20150106085 | Lindahl | Apr 2015 | A1 |
| 20150106093 | Weeks et al. | Apr 2015 | A1 |
| 20150106737 | Montoy-Wilson et al. | Apr 2015 | A1 |
| 20150112684 | Scheffer et al. | Apr 2015 | A1 |
| 20150113407 | Hoffert et al. | Apr 2015 | A1 |
| 20150113435 | Phillips | Apr 2015 | A1 |
| 20150113454 | McLaughlin | Apr 2015 | A1 |
| 20150120296 | Stern et al. | Apr 2015 | A1 |
| 20150120641 | Soon-Shiong et al. | Apr 2015 | A1 |
| 20150120723 | Deshmukh et al. | Apr 2015 | A1 |
| 20150121216 | Brown et al. | Apr 2015 | A1 |
| 20150121227 | Peng | Apr 2015 | A1 |
| 20150123898 | Kim et al. | May 2015 | A1 |
| 20150127336 | Lei et al. | May 2015 | A1 |
| 20150127337 | Heigold et al. | May 2015 | A1 |
| 20150127348 | Follis | May 2015 | A1 |
| 20150127350 | Agiomyrgiannakis | May 2015 | A1 |
| 20150128058 | Anajwala | May 2015 | A1 |
| 20150133049 | Lee et al. | May 2015 | A1 |
| 20150133109 | Freeman et al. | May 2015 | A1 |
| 20150134318 | Cuthbert et al. | May 2015 | A1 |
| 20150134322 | Cuthbert et al. | May 2015 | A1 |
| 20150134323 | Cuthbert et al. | May 2015 | A1 |
| 20150134334 | Sachidanandam et al. | May 2015 | A1 |
| 20150135085 | Shoham et al. | May 2015 | A1 |
| 20150135123 | Carr et al. | May 2015 | A1 |
| 20150140934 | Abdurrahman et al. | May 2015 | A1 |
| 20150140990 | Kim et al. | May 2015 | A1 |
| 20150141150 | Zha | May 2015 | A1 |
| 20150142420 | Sarikaya et al. | May 2015 | A1 |
| 20150142438 | Dai et al. | May 2015 | A1 |
| 20150142440 | Parkinson et al. | May 2015 | A1 |
| 20150142447 | Kennewick et al. | May 2015 | A1 |
| 20150142851 | Gupta et al. | May 2015 | A1 |
| 20150143419 | Bhagwat et al. | May 2015 | A1 |
| 20150148013 | Baldwin et al. | May 2015 | A1 |
| 20150149146 | Abramovitz et al. | May 2015 | A1 |
| 20150149177 | Kalns et al. | May 2015 | A1 |
| 20150149182 | Kalns et al. | May 2015 | A1 |
| 20150149354 | McCoy | May 2015 | A1 |
| 20150149469 | Xu et al. | May 2015 | A1 |
| 20150149899 | Bernstein et al. | May 2015 | A1 |
| 20150149964 | Bernstein et al. | May 2015 | A1 |
| 20150154001 | Knox et al. | Jun 2015 | A1 |
| 20150154185 | Waibel | Jun 2015 | A1 |
| 20150154976 | Mutagi | Jun 2015 | A1 |
| 20150160855 | Bi | Jun 2015 | A1 |
| 20150161291 | Gur et al. | Jun 2015 | A1 |
| 20150161370 | North et al. | Jun 2015 | A1 |
| 20150161521 | Shah et al. | Jun 2015 | A1 |
| 20150161989 | Hsu et al. | Jun 2015 | A1 |
| 20150162000 | Di Censo et al. | Jun 2015 | A1 |
| 20150162001 | Kar et al. | Jun 2015 | A1 |
| 20150162006 | Kummer | Jun 2015 | A1 |
| 20150163558 | Wheatley | Jun 2015 | A1 |
| 20150169081 | Neels et al. | Jun 2015 | A1 |
| 20150169195 | Choi | Jun 2015 | A1 |
| 20150169284 | Quast et al. | Jun 2015 | A1 |
| 20150169336 | Harper et al. | Jun 2015 | A1 |
| 20150169696 | Krishnappa et al. | Jun 2015 | A1 |
| 20150170073 | Baker | Jun 2015 | A1 |
| 20150170664 | Doherty et al. | Jun 2015 | A1 |
| 20150172262 | Ortiz, Jr. et al. | Jun 2015 | A1 |
| 20150172463 | Quast et al. | Jun 2015 | A1 |
| 20150178388 | Winnemoeller et al. | Jun 2015 | A1 |
| 20150178785 | Salonen | Jun 2015 | A1 |
| 20150179168 | Hakkani-Tur et al. | Jun 2015 | A1 |
| 20150179176 | Ryu et al. | Jun 2015 | A1 |
| 20150181285 | Zhang et al. | Jun 2015 | A1 |
| 20150185718 | Tappan et al. | Jul 2015 | A1 |
| 20150185964 | Stout | Jul 2015 | A1 |
| 20150185993 | Wheatley et al. | Jul 2015 | A1 |
| 20150185996 | Brown et al. | Jul 2015 | A1 |
| 20150186012 | Coleman et al. | Jul 2015 | A1 |
| 20150186110 | Kannan | Jul 2015 | A1 |
| 20150186154 | Brown et al. | Jul 2015 | A1 |
| 20150186155 | Brown et al. | Jul 2015 | A1 |
| 20150186156 | Brown et al. | Jul 2015 | A1 |
| 20150186351 | Hicks et al. | Jul 2015 | A1 |
| 20150186538 | Yan et al. | Jul 2015 | A1 |
| 20150186783 | Byrne et al. | Jul 2015 | A1 |
| 20150186892 | Zhang et al. | Jul 2015 | A1 |
| 20150187355 | Parkinson et al. | Jul 2015 | A1 |
| 20150187369 | Dadu et al. | Jul 2015 | A1 |
| 20150189362 | Lee et al. | Jul 2015 | A1 |
| 20150193379 | Mehta | Jul 2015 | A1 |
| 20150193391 | Khvostichenko et al. | Jul 2015 | A1 |
| 20150193392 | Greenblatt et al. | Jul 2015 | A1 |
| 20150194152 | Katuri et al. | Jul 2015 | A1 |
| 20150194165 | Faaborg et al. | Jul 2015 | A1 |
| 20150195379 | Zhang et al. | Jul 2015 | A1 |
| 20150195606 | McDevitt | Jul 2015 | A1 |
| 20150199077 | Zuger et al. | Jul 2015 | A1 |
| 20150199960 | Huo et al. | Jul 2015 | A1 |
| 20150199965 | Leak et al. | Jul 2015 | A1 |
| 20150199967 | Reddy et al. | Jul 2015 | A1 |
| 20150200879 | Wu et al. | Jul 2015 | A1 |
| 20150201064 | Bells et al. | Jul 2015 | A1 |
| 20150201077 | Konig et al. | Jul 2015 | A1 |
| 20150205425 | Kuscher et al. | Jul 2015 | A1 |
| 20150205568 | Matsuoka | Jul 2015 | A1 |
| 20150205632 | Gaster | Jul 2015 | A1 |
| 20150205858 | Xie et al. | Jul 2015 | A1 |
| 20150206529 | Kwon et al. | Jul 2015 | A1 |
| 20150208226 | Kuusilinna et al. | Jul 2015 | A1 |
| 20150212791 | Kumar et al. | Jul 2015 | A1 |
| 20150213140 | Volkert | Jul 2015 | A1 |
| 20150213796 | Waltermann et al. | Jul 2015 | A1 |
| 20150215258 | Nowakowski et al. | Jul 2015 | A1 |
| 20150215350 | Slayton et al. | Jul 2015 | A1 |
| 20150217870 | Mccullough et al. | Aug 2015 | A1 |
| 20150220264 | Lewis et al. | Aug 2015 | A1 |
| 20150220507 | Mohajer et al. | Aug 2015 | A1 |
| 20150220715 | Kim et al. | Aug 2015 | A1 |
| 20150220972 | Subramanya et al. | Aug 2015 | A1 |
| 20150221302 | Han et al. | Aug 2015 | A1 |
| 20150221304 | Stewart | Aug 2015 | A1 |
| 20150221307 | Shah et al. | Aug 2015 | A1 |
| 20150222586 | Ebersman et al. | Aug 2015 | A1 |
| 20150224848 | Eisenhour | Aug 2015 | A1 |
| 20150227505 | Morimoto | Aug 2015 | A1 |
| 20150227633 | Shapira | Aug 2015 | A1 |
| 20150228274 | Leppanen et al. | Aug 2015 | A1 |
| 20150228275 | Watanabe et al. | Aug 2015 | A1 |
| 20150228281 | Raniere | Aug 2015 | A1 |
| 20150228282 | Evrard | Aug 2015 | A1 |
| 20150228283 | Ehsani et al. | Aug 2015 | A1 |
| 20150228292 | Goldstein et al. | Aug 2015 | A1 |
| 20150230095 | Smith et al. | Aug 2015 | A1 |
| 20150234556 | Shaofeng et al. | Aug 2015 | A1 |
| 20150234636 | Barnes, Jr. | Aug 2015 | A1 |
| 20150234800 | Patrick et al. | Aug 2015 | A1 |
| 20150235434 | Miller et al. | Aug 2015 | A1 |
| 20150235540 | Verna et al. | Aug 2015 | A1 |
| 20150237301 | Shi et al. | Aug 2015 | A1 |
| 20150242091 | Lu et al. | Aug 2015 | A1 |
| 20150242385 | Bao et al. | Aug 2015 | A1 |
| 20150243278 | Kibre et al. | Aug 2015 | A1 |
| 20150243279 | Morse et al. | Aug 2015 | A1 |
| 20150243283 | Halash et al. | Aug 2015 | A1 |
| 20150244665 | Choi et al. | Aug 2015 | A1 |
| 20150245154 | Dadu et al. | Aug 2015 | A1 |
| 20150248494 | Mital | Sep 2015 | A1 |
| 20150248651 | Akutagawa et al. | Sep 2015 | A1 |
| 20150248886 | Sarikaya et al. | Sep 2015 | A1 |
| 20150249715 | Helvik et al. | Sep 2015 | A1 |
| 20150253146 | Annapureddy et al. | Sep 2015 | A1 |
| 20150253885 | Kagan et al. | Sep 2015 | A1 |
| 20150254057 | Klein et al. | Sep 2015 | A1 |
| 20150254058 | Klein et al. | Sep 2015 | A1 |
| 20150254333 | Fife et al. | Sep 2015 | A1 |
| 20150255068 | Kim et al. | Sep 2015 | A1 |
| 20150255071 | Chiba | Sep 2015 | A1 |
| 20150256873 | Klein et al. | Sep 2015 | A1 |
| 20150261298 | Li | Sep 2015 | A1 |
| 20150261496 | Faaborg et al. | Sep 2015 | A1 |
| 20150261850 | Mittal | Sep 2015 | A1 |
| 20150261944 | Hosom et al. | Sep 2015 | A1 |
| 20150262443 | Chong | Sep 2015 | A1 |
| 20150262573 | Brooks et al. | Sep 2015 | A1 |
| 20150262583 | Kanda et al. | Sep 2015 | A1 |
| 20150269139 | McAteer et al. | Sep 2015 | A1 |
| 20150269617 | Mikurak | Sep 2015 | A1 |
| 20150269677 | Milne | Sep 2015 | A1 |
| 20150269943 | VanBlon et al. | Sep 2015 | A1 |
| 20150277574 | Jain et al. | Oct 2015 | A1 |
| 20150278199 | Hazen et al. | Oct 2015 | A1 |
| 20150278348 | Paruchuri et al. | Oct 2015 | A1 |
| 20150278370 | Stratvert et al. | Oct 2015 | A1 |
| 20150278737 | Chen Huebscher et al. | Oct 2015 | A1 |
| 20150279354 | Gruenstein et al. | Oct 2015 | A1 |
| 20150279358 | Kingsbury et al. | Oct 2015 | A1 |
| 20150279360 | Mengibar et al. | Oct 2015 | A1 |
| 20150279366 | Krestnikov et al. | Oct 2015 | A1 |
| 20150281380 | Wang et al. | Oct 2015 | A1 |
| 20150281401 | Le et al. | Oct 2015 | A1 |
| 20150286627 | Chang et al. | Oct 2015 | A1 |
| 20150286716 | Snibbe et al. | Oct 2015 | A1 |
| 20150286937 | Hildebrand | Oct 2015 | A1 |
| 20150287401 | Lee et al. | Oct 2015 | A1 |
| 20150287408 | Svendsen et al. | Oct 2015 | A1 |
| 20150287409 | Jang | Oct 2015 | A1 |
| 20150287411 | Kojima et al. | Oct 2015 | A1 |
| 20150288629 | Choi et al. | Oct 2015 | A1 |
| 20150294086 | Kare et al. | Oct 2015 | A1 |
| 20150294377 | Chow | Oct 2015 | A1 |
| 20150294516 | Chiang | Oct 2015 | A1 |
| 20150294670 | Roblek et al. | Oct 2015 | A1 |
| 20150295915 | Xiu | Oct 2015 | A1 |
| 20150296065 | Narita et al. | Oct 2015 | A1 |
| 20150301796 | Visser et al. | Oct 2015 | A1 |
| 20150302316 | Buryak et al. | Oct 2015 | A1 |
| 20150302855 | Kim et al. | Oct 2015 | A1 |
| 20150302856 | Kim et al. | Oct 2015 | A1 |
| 20150302857 | Yamada | Oct 2015 | A1 |
| 20150302870 | Burke et al. | Oct 2015 | A1 |
| 20150308470 | Graham et al. | Oct 2015 | A1 |
| 20150309691 | Seo et al. | Oct 2015 | A1 |
| 20150309997 | Lee et al. | Oct 2015 | A1 |
| 20150310114 | Ryger et al. | Oct 2015 | A1 |
| 20150310852 | Spizzo et al. | Oct 2015 | A1 |
| 20150310858 | Li et al. | Oct 2015 | A1 |
| 20150310862 | Dauphin et al. | Oct 2015 | A1 |
| 20150310879 | Buchanan et al. | Oct 2015 | A1 |
| 20150310888 | Chen | Oct 2015 | A1 |
| 20150312182 | Langholz | Oct 2015 | A1 |
| 20150312409 | Czarnecki et al. | Oct 2015 | A1 |
| 20150314454 | Breazeal et al. | Nov 2015 | A1 |
| 20150317069 | Clements et al. | Nov 2015 | A1 |
| 20150317310 | Eiche et al. | Nov 2015 | A1 |
| 20150319264 | Allen et al. | Nov 2015 | A1 |
| 20150319411 | Kasmir et al. | Nov 2015 | A1 |
| 20150324041 | Varley et al. | Nov 2015 | A1 |
| 20150324334 | Lee et al. | Nov 2015 | A1 |
| 20150324362 | Glass et al. | Nov 2015 | A1 |
| 20150331664 | Osawa et al. | Nov 2015 | A1 |
| 20150331711 | Huang et al. | Nov 2015 | A1 |
| 20150332667 | Mason | Nov 2015 | A1 |
| 20150334346 | Cheatham, III et al. | Nov 2015 | A1 |
| 20150339049 | Kasemset et al. | Nov 2015 | A1 |
| 20150339391 | Kang et al. | Nov 2015 | A1 |
| 20150340033 | Di Fabbrizio et al. | Nov 2015 | A1 |
| 20150340034 | Schalkwyk et al. | Nov 2015 | A1 |
| 20150340040 | Mun et al. | Nov 2015 | A1 |
| 20150340042 | Sejnoha et al. | Nov 2015 | A1 |
| 20150341717 | Song et al. | Nov 2015 | A1 |
| 20150346845 | Di Censo et al. | Dec 2015 | A1 |
| 20150347086 | Liedholm et al. | Dec 2015 | A1 |
| 20150347381 | Bellegarda | Dec 2015 | A1 |
| 20150347382 | Dolfing et al. | Dec 2015 | A1 |
| 20150347383 | Willmore et al. | Dec 2015 | A1 |
| 20150347385 | Flor et al. | Dec 2015 | A1 |
| 20150347393 | Futrell et al. | Dec 2015 | A1 |
| 20150347552 | Habouzit et al. | Dec 2015 | A1 |
| 20150347733 | Tsou et al. | Dec 2015 | A1 |
| 20150347985 | Gross et al. | Dec 2015 | A1 |
| 20150348533 | Saddler et al. | Dec 2015 | A1 |
| 20150348547 | Paulik et al. | Dec 2015 | A1 |
| 20150348548 | Piernot et al. | Dec 2015 | A1 |
| 20150348549 | Giuli et al. | Dec 2015 | A1 |
| 20150348551 | Gruber et al. | Dec 2015 | A1 |
| 20150348554 | Orr et al. | Dec 2015 | A1 |
| 20150348555 | Sugita | Dec 2015 | A1 |
| 20150348565 | Rhoten et al. | Dec 2015 | A1 |
| 20150349934 | Pollack et al. | Dec 2015 | A1 |
| 20150350031 | Burks et al. | Dec 2015 | A1 |
| 20150350147 | Shepherd et al. | Dec 2015 | A1 |
| 20150350342 | Thorpe et al. | Dec 2015 | A1 |
| 20150350594 | Mate et al. | Dec 2015 | A1 |
| 20150352999 | Bando et al. | Dec 2015 | A1 |
| 20150355879 | Beckhardt et al. | Dec 2015 | A1 |
| 20150356410 | Faith et al. | Dec 2015 | A1 |
| 20150363587 | Ahn et al. | Dec 2015 | A1 |
| 20150364128 | Zhao et al. | Dec 2015 | A1 |
| 20150364140 | Thörn | Dec 2015 | A1 |
| 20150365251 | Kinoshita et al. | Dec 2015 | A1 |
| 20150370455 | Van Os et al. | Dec 2015 | A1 |
| 20150370531 | Faaborg | Dec 2015 | A1 |
| 20150370780 | Wang et al. | Dec 2015 | A1 |
| 20150370787 | Akbacak et al. | Dec 2015 | A1 |
| 20150370884 | Hurley et al. | Dec 2015 | A1 |
| 20150371215 | Zhou et al. | Dec 2015 | A1 |
| 20150371529 | Dolecki | Dec 2015 | A1 |
| 20150371639 | Foerster et al. | Dec 2015 | A1 |
| 20150371663 | Gustafson et al. | Dec 2015 | A1 |
| 20150371664 | Bar-or et al. | Dec 2015 | A1 |
| 20150371665 | Naik et al. | Dec 2015 | A1 |
| 20150373183 | Woolsey et al. | Dec 2015 | A1 |
| 20150379118 | Wickenkamp et al. | Dec 2015 | A1 |
| 20150379414 | Yeh et al. | Dec 2015 | A1 |
| 20150379993 | Subhojit et al. | Dec 2015 | A1 |
| 20150381923 | Wickenkamp et al. | Dec 2015 | A1 |
| 20150382047 | Van Os et al. | Dec 2015 | A1 |
| 20150382079 | Lister et al. | Dec 2015 | A1 |
| 20150382147 | Clark et al. | Dec 2015 | A1 |
| 20160004499 | Kim et al. | Jan 2016 | A1 |
| 20160004690 | Bangalore et al. | Jan 2016 | A1 |
| 20160005320 | deCharms et al. | Jan 2016 | A1 |
| 20160006795 | Yunten | Jan 2016 | A1 |
| 20160012038 | Edwards et al. | Jan 2016 | A1 |
| 20160014476 | Caliendo, Jr. et al. | Jan 2016 | A1 |
| 20160018872 | Tu et al. | Jan 2016 | A1 |
| 20160018900 | Tu et al. | Jan 2016 | A1 |
| 20160018959 | Yamashita et al. | Jan 2016 | A1 |
| 20160019886 | Hong | Jan 2016 | A1 |
| 20160019896 | Alvarez Guevara et al. | Jan 2016 | A1 |
| 20160021414 | Padi et al. | Jan 2016 | A1 |
| 20160026242 | Burns et al. | Jan 2016 | A1 |
| 20160026258 | Ou et al. | Jan 2016 | A1 |
| 20160027431 | Kurzweil et al. | Jan 2016 | A1 |
| 20160028666 | Li | Jan 2016 | A1 |
| 20160028802 | Balasingh et al. | Jan 2016 | A1 |
| 20160029316 | Mohan et al. | Jan 2016 | A1 |
| 20160034042 | Joo | Feb 2016 | A1 |
| 20160034447 | Shin et al. | Feb 2016 | A1 |
| 20160034811 | Paulik et al. | Feb 2016 | A1 |
| 20160036750 | Yuan et al. | Feb 2016 | A1 |
| 20160036953 | Lee et al. | Feb 2016 | A1 |
| 20160041809 | Clayton et al. | Feb 2016 | A1 |
| 20160042735 | Vibbert et al. | Feb 2016 | A1 |
| 20160042748 | Jain et al. | Feb 2016 | A1 |
| 20160043905 | Fiedler | Feb 2016 | A1 |
| 20160048666 | Dey et al. | Feb 2016 | A1 |
| 20160050254 | Rao et al. | Feb 2016 | A1 |
| 20160055422 | Li | Feb 2016 | A1 |
| 20160057203 | Gärdenfors et al. | Feb 2016 | A1 |
| 20160057475 | Liu | Feb 2016 | A1 |
| 20160061623 | Pahwa et al. | Mar 2016 | A1 |
| 20160062459 | Publicover et al. | Mar 2016 | A1 |
| 20160062605 | Agarwal et al. | Mar 2016 | A1 |
| 20160063094 | Udupa et al. | Mar 2016 | A1 |
| 20160063095 | Nassar et al. | Mar 2016 | A1 |
| 20160063998 | Krishnamoorthy et al. | Mar 2016 | A1 |
| 20160065155 | Bharj et al. | Mar 2016 | A1 |
| 20160065626 | Jain et al. | Mar 2016 | A1 |
| 20160066020 | Mountain | Mar 2016 | A1 |
| 20160070581 | Soon-Shiong | Mar 2016 | A1 |
| 20160071516 | Lee et al. | Mar 2016 | A1 |
| 20160071517 | Beaver et al. | Mar 2016 | A1 |
| 20160071520 | Hayakawa | Mar 2016 | A1 |
| 20160071521 | Haughay | Mar 2016 | A1 |
| 20160072940 | Cronin | Mar 2016 | A1 |
| 20160077794 | Kim et al. | Mar 2016 | A1 |
| 20160078359 | Csurka et al. | Mar 2016 | A1 |
| 20160078860 | Paulik et al. | Mar 2016 | A1 |
| 20160080165 | Ehsani et al. | Mar 2016 | A1 |
| 20160080475 | Singh et al. | Mar 2016 | A1 |
| 20160085295 | Shimy et al. | Mar 2016 | A1 |
| 20160085827 | Chadha et al. | Mar 2016 | A1 |
| 20160086116 | Rao et al. | Mar 2016 | A1 |
| 20160086599 | Kurata et al. | Mar 2016 | A1 |
| 20160088335 | Zucchetta | Mar 2016 | A1 |
| 20160091871 | Marti et al. | Mar 2016 | A1 |
| 20160091967 | Prokofieva et al. | Mar 2016 | A1 |
| 20160092046 | Hong et al. | Mar 2016 | A1 |
| 20160092434 | Bellegarda | Mar 2016 | A1 |
| 20160092447 | Pathurudeen et al. | Mar 2016 | A1 |
| 20160092766 | Sainath et al. | Mar 2016 | A1 |
| 20160093291 | Kim | Mar 2016 | A1 |
| 20160093298 | Naik et al. | Mar 2016 | A1 |
| 20160093301 | Bellegarda et al. | Mar 2016 | A1 |
| 20160093304 | Kim et al. | Mar 2016 | A1 |
| 20160094700 | Lee et al. | Mar 2016 | A1 |
| 20160094889 | Venkataraman et al. | Mar 2016 | A1 |
| 20160094979 | Naik et al. | Mar 2016 | A1 |
| 20160098991 | Luo et al. | Apr 2016 | A1 |
| 20160098992 | Renard et al. | Apr 2016 | A1 |
| 20160099892 | Palakovich et al. | Apr 2016 | A1 |
| 20160099984 | Karagiannis et al. | Apr 2016 | A1 |
| 20160104480 | Sharifi | Apr 2016 | A1 |
| 20160104486 | Penilla et al. | Apr 2016 | A1 |
| 20160105308 | Dutt | Apr 2016 | A1 |
| 20160111091 | Bakish | Apr 2016 | A1 |
| 20160112746 | Zhang et al. | Apr 2016 | A1 |
| 20160112792 | Lee et al. | Apr 2016 | A1 |
| 20160117386 | Ajmera et al. | Apr 2016 | A1 |
| 20160118048 | Heide | Apr 2016 | A1 |
| 20160119338 | Cheyer | Apr 2016 | A1 |
| 20160125048 | Hamada | May 2016 | A1 |
| 20160125071 | Gabbai | May 2016 | A1 |
| 20160132046 | Beoughter et al. | May 2016 | A1 |
| 20160132290 | Raux | May 2016 | A1 |
| 20160132484 | Nauze et al. | May 2016 | A1 |
| 20160132488 | Clark et al. | May 2016 | A1 |
| 20160133254 | Vogel et al. | May 2016 | A1 |
| 20160139662 | Dabhade | May 2016 | A1 |
| 20160140951 | Agiomyrgiannakis et al. | May 2016 | A1 |
| 20160140962 | Sharifi | May 2016 | A1 |
| 20160147725 | Patten et al. | May 2016 | A1 |
| 20160147739 | Lim et al. | May 2016 | A1 |
| 20160148610 | Kennewick, Jr. et al. | May 2016 | A1 |
| 20160148612 | Guo et al. | May 2016 | A1 |
| 20160148613 | Kwon et al. | May 2016 | A1 |
| 20160149966 | Remash et al. | May 2016 | A1 |
| 20160150020 | Farmer et al. | May 2016 | A1 |
| 20160151668 | Barnes et al. | Jun 2016 | A1 |
| 20160154624 | Son et al. | Jun 2016 | A1 |
| 20160154880 | Hoarty | Jun 2016 | A1 |
| 20160155442 | Kannan et al. | Jun 2016 | A1 |
| 20160155443 | Khan et al. | Jun 2016 | A1 |
| 20160156574 | Hum et al. | Jun 2016 | A1 |
| 20160156990 | Miccoy et al. | Jun 2016 | A1 |
| 20160162456 | Munro et al. | Jun 2016 | A1 |
| 20160163311 | Crook et al. | Jun 2016 | A1 |
| 20160163312 | Naik et al. | Jun 2016 | A1 |
| 20160170710 | Kim et al. | Jun 2016 | A1 |
| 20160170966 | Kolo | Jun 2016 | A1 |
| 20160171980 | Liddell et al. | Jun 2016 | A1 |
| 20160173578 | Sharma et al. | Jun 2016 | A1 |
| 20160173617 | Allinson | Jun 2016 | A1 |
| 20160173929 | Klappert | Jun 2016 | A1 |
| 20160173960 | Snibbe et al. | Jun 2016 | A1 |
| 20160179462 | Bjorkengren | Jun 2016 | A1 |
| 20160179464 | Reddy et al. | Jun 2016 | A1 |
| 20160179787 | Deleeuw | Jun 2016 | A1 |
| 20160180840 | Siddiq et al. | Jun 2016 | A1 |
| 20160180844 | Vanblon et al. | Jun 2016 | A1 |
| 20160182410 | Janakiraman et al. | Jun 2016 | A1 |
| 20160182709 | Kim et al. | Jun 2016 | A1 |
| 20160188181 | Smith | Jun 2016 | A1 |
| 20160188738 | Gruber et al. | Jun 2016 | A1 |
| 20160189198 | Daniel et al. | Jun 2016 | A1 |
| 20160189715 | Nishikawa | Jun 2016 | A1 |
| 20160189717 | Kannan et al. | Jun 2016 | A1 |
| 20160196110 | Yehoshua et al. | Jul 2016 | A1 |
| 20160198319 | Huang et al. | Jul 2016 | A1 |
| 20160203002 | Kannan et al. | Jul 2016 | A1 |
| 20160203193 | Kevin et al. | Jul 2016 | A1 |
| 20160210551 | Lee et al. | Jul 2016 | A1 |
| 20160210981 | Lee | Jul 2016 | A1 |
| 20160212206 | Wu et al. | Jul 2016 | A1 |
| 20160212208 | Kulkarni et al. | Jul 2016 | A1 |
| 20160212488 | Os et al. | Jul 2016 | A1 |
| 20160217784 | Gelfenbeyn et al. | Jul 2016 | A1 |
| 20160217794 | Imoto et al. | Jul 2016 | A1 |
| 20160224540 | Stewart et al. | Aug 2016 | A1 |
| 20160224559 | Hicks et al. | Aug 2016 | A1 |
| 20160224774 | Pender | Aug 2016 | A1 |
| 20160225372 | Cheung et al. | Aug 2016 | A1 |
| 20160226956 | Hong et al. | Aug 2016 | A1 |
| 20160227107 | Beaumont | Aug 2016 | A1 |
| 20160227633 | Sun et al. | Aug 2016 | A1 |
| 20160232500 | Wang et al. | Aug 2016 | A1 |
| 20160234206 | Tunnell et al. | Aug 2016 | A1 |
| 20160239480 | Larcheveque et al. | Aug 2016 | A1 |
| 20160239568 | Packer et al. | Aug 2016 | A1 |
| 20160239645 | Heo et al. | Aug 2016 | A1 |
| 20160239848 | Chang et al. | Aug 2016 | A1 |
| 20160240187 | Fleizach et al. | Aug 2016 | A1 |
| 20160240189 | Lee et al. | Aug 2016 | A1 |
| 20160240192 | Raghuvir | Aug 2016 | A1 |
| 20160242148 | Reed | Aug 2016 | A1 |
| 20160247061 | Trask et al. | Aug 2016 | A1 |
| 20160249319 | Dotan-Cohen et al. | Aug 2016 | A1 |
| 20160253312 | Rhodes | Sep 2016 | A1 |
| 20160253528 | Gao et al. | Sep 2016 | A1 |
| 20160259623 | Sumner et al. | Sep 2016 | A1 |
| 20160259656 | Sumner et al. | Sep 2016 | A1 |
| 20160259779 | Labský et al. | Sep 2016 | A1 |
| 20160260431 | Newendorp et al. | Sep 2016 | A1 |
| 20160260433 | Sumner et al. | Sep 2016 | A1 |
| 20160260434 | Gelfenbeyn et al. | Sep 2016 | A1 |
| 20160260436 | Lemay et al. | Sep 2016 | A1 |
| 20160262442 | Davila et al. | Sep 2016 | A1 |
| 20160266871 | Schmid et al. | Sep 2016 | A1 |
| 20160267904 | Biadsy et al. | Sep 2016 | A1 |
| 20160269540 | Butcher et al. | Sep 2016 | A1 |
| 20160274938 | Strinati et al. | Sep 2016 | A1 |
| 20160275941 | Bellegarda et al. | Sep 2016 | A1 |
| 20160275947 | Li et al. | Sep 2016 | A1 |
| 20160282824 | Smallwood et al. | Sep 2016 | A1 |
| 20160282956 | Ouyang et al. | Sep 2016 | A1 |
| 20160283185 | Mclaren et al. | Sep 2016 | A1 |
| 20160284005 | Daniel et al. | Sep 2016 | A1 |
| 20160284199 | Dotan-Cohen et al. | Sep 2016 | A1 |
| 20160285808 | Franklin et al. | Sep 2016 | A1 |
| 20160286045 | Shaltiel et al. | Sep 2016 | A1 |
| 20160291831 | Baek | Oct 2016 | A1 |
| 20160293157 | Chen et al. | Oct 2016 | A1 |
| 20160293167 | Chen et al. | Oct 2016 | A1 |
| 20160293168 | Chen | Oct 2016 | A1 |
| 20160294755 | Prabhu | Oct 2016 | A1 |
| 20160294813 | Zou | Oct 2016 | A1 |
| 20160299685 | Zhai et al. | Oct 2016 | A1 |
| 20160299882 | Hegerty et al. | Oct 2016 | A1 |
| 20160299883 | Zhu et al. | Oct 2016 | A1 |
| 20160299977 | Hreha | Oct 2016 | A1 |
| 20160300571 | Foerster et al. | Oct 2016 | A1 |
| 20160301639 | Liu et al. | Oct 2016 | A1 |
| 20160306683 | Standley et al. | Oct 2016 | A1 |
| 20160307566 | Bellegarda | Oct 2016 | A1 |
| 20160308799 | Schubert et al. | Oct 2016 | A1 |
| 20160309035 | Li | Oct 2016 | A1 |
| 20160313906 | Kilchenko et al. | Oct 2016 | A1 |
| 20160314788 | Jitkoff et al. | Oct 2016 | A1 |
| 20160314789 | Marcheret et al. | Oct 2016 | A1 |
| 20160314792 | Alvarez et al. | Oct 2016 | A1 |
| 20160315996 | Ha et al. | Oct 2016 | A1 |
| 20160316349 | Lee et al. | Oct 2016 | A1 |
| 20160317924 | Tanaka et al. | Nov 2016 | A1 |
| 20160320838 | Teller et al. | Nov 2016 | A1 |
| 20160321239 | Iso-Sipilä et al. | Nov 2016 | A1 |
| 20160321243 | Walia et al. | Nov 2016 | A1 |
| 20160321261 | Spasojevic et al. | Nov 2016 | A1 |
| 20160321358 | Kanani et al. | Nov 2016 | A1 |
| 20160322043 | Bellegarda | Nov 2016 | A1 |
| 20160322044 | Jung et al. | Nov 2016 | A1 |
| 20160322045 | Hatfield et al. | Nov 2016 | A1 |
| 20160322048 | Amano et al. | Nov 2016 | A1 |
| 20160322050 | Wang et al. | Nov 2016 | A1 |
| 20160322055 | Sainath et al. | Nov 2016 | A1 |
| 20160328134 | Xu | Nov 2016 | A1 |
| 20160328147 | Zhang et al. | Nov 2016 | A1 |
| 20160328205 | Agrawal et al. | Nov 2016 | A1 |
| 20160328893 | Cordova et al. | Nov 2016 | A1 |
| 20160329060 | Ito et al. | Nov 2016 | A1 |
| 20160334973 | Reckhow et al. | Nov 2016 | A1 |
| 20160335138 | Surti et al. | Nov 2016 | A1 |
| 20160335139 | Hurley et al. | Nov 2016 | A1 |
| 20160335532 | Sanghavi et al. | Nov 2016 | A1 |
| 20160336007 | Hanazawa et al. | Nov 2016 | A1 |
| 20160336010 | Lindahl | Nov 2016 | A1 |
| 20160336011 | Koll et al. | Nov 2016 | A1 |
| 20160336024 | Choi et al. | Nov 2016 | A1 |
| 20160337299 | Lane et al. | Nov 2016 | A1 |
| 20160337301 | Rollins et al. | Nov 2016 | A1 |
| 20160342317 | Lim et al. | Nov 2016 | A1 |
| 20160342685 | Basu et al. | Nov 2016 | A1 |
| 20160342781 | Jeon | Nov 2016 | A1 |
| 20160350650 | Leeman-Munk et al. | Dec 2016 | A1 |
| 20160350812 | Priness et al. | Dec 2016 | A1 |
| 20160351190 | Piernot et al. | Dec 2016 | A1 |
| 20160352567 | Robbins et al. | Dec 2016 | A1 |
| 20160352924 | Senarath et al. | Dec 2016 | A1 |
| 20160357304 | Hatori et al. | Dec 2016 | A1 |
| 20160357728 | Bellegarda et al. | Dec 2016 | A1 |
| 20160357790 | Elkington et al. | Dec 2016 | A1 |
| 20160357861 | Carlhian et al. | Dec 2016 | A1 |
| 20160357870 | Hentschel et al. | Dec 2016 | A1 |
| 20160358598 | Williams et al. | Dec 2016 | A1 |
| 20160358600 | Nallasamy et al. | Dec 2016 | A1 |
| 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 |
| 20160372119 | Sak et al. | Dec 2016 | A1 |
| 20160378747 | Orr et al. | Dec 2016 | A1 |
| 20160379091 | Lin et al. | Dec 2016 | A1 |
| 20160379105 | Moore, Jr. | Dec 2016 | A1 |
| 20160379626 | Deisher et al. | Dec 2016 | A1 |
| 20160379632 | Hoffmeister et al. | Dec 2016 | A1 |
| 20160379633 | Lehman et al. | Dec 2016 | A1 |
| 20160379639 | Weinstein et al. | Dec 2016 | A1 |
| 20160379641 | Liu et al. | Dec 2016 | A1 |
| 20170000348 | Karsten et al. | Jan 2017 | A1 |
| 20170003931 | Dvortsov et al. | Jan 2017 | A1 |
| 20170004209 | Johl et al. | Jan 2017 | A1 |
| 20170004824 | Yoo et al. | Jan 2017 | A1 |
| 20170005818 | Gould | Jan 2017 | A1 |
| 20170006329 | Jang et al. | Jan 2017 | A1 |
| 20170011091 | Chehreghani | Jan 2017 | A1 |
| 20170011279 | Soldevila et al. | Jan 2017 | A1 |
| 20170011303 | Annapureddy et al. | Jan 2017 | A1 |
| 20170011742 | Jing et al. | Jan 2017 | A1 |
| 20170013124 | Havelka et al. | Jan 2017 | A1 |
| 20170013331 | Watanabe et al. | Jan 2017 | A1 |
| 20170018271 | Khan et al. | Jan 2017 | A1 |
| 20170019987 | Dragone et al. | Jan 2017 | A1 |
| 20170023963 | Davis et al. | Jan 2017 | A1 |
| 20170025124 | Mixter et al. | Jan 2017 | A1 |
| 20170026318 | Daniel et al. | Jan 2017 | A1 |
| 20170026509 | Rand | Jan 2017 | A1 |
| 20170027522 | Van Hasselt et al. | Feb 2017 | A1 |
| 20170031576 | Saoji et al. | Feb 2017 | A1 |
| 20170032783 | Lord et al. | Feb 2017 | A1 |
| 20170032787 | Dayal | Feb 2017 | A1 |
| 20170032791 | Elson et al. | Feb 2017 | A1 |
| 20170039283 | Bennett et al. | Feb 2017 | A1 |
| 20170039475 | Cheyer et al. | Feb 2017 | A1 |
| 20170040002 | Basson et al. | Feb 2017 | A1 |
| 20170041388 | Tal et al. | Feb 2017 | A1 |
| 20170046025 | Dascola et al. | Feb 2017 | A1 |
| 20170047063 | Ohmura et al. | Feb 2017 | A1 |
| 20170052760 | Johnson et al. | Feb 2017 | A1 |
| 20170053652 | Choi et al. | Feb 2017 | A1 |
| 20170055895 | Jardins et al. | Mar 2017 | A1 |
| 20170060853 | Lee et al. | Mar 2017 | A1 |
| 20170061423 | Bryant et al. | Mar 2017 | A1 |
| 20170068423 | Napolitano et al. | Mar 2017 | A1 |
| 20170068513 | Stasior et al. | Mar 2017 | A1 |
| 20170068550 | Zeitlin | Mar 2017 | A1 |
| 20170068670 | Orr et al. | Mar 2017 | A1 |
| 20170069308 | Aleksic et al. | Mar 2017 | A1 |
| 20170069321 | Toiyama | Mar 2017 | A1 |
| 20170069327 | Heigold et al. | Mar 2017 | A1 |
| 20170075653 | Dawidowsky et al. | Mar 2017 | A1 |
| 20170076518 | Patterson et al. | Mar 2017 | A1 |
| 20170076720 | Gopalan et al. | Mar 2017 | A1 |
| 20170076721 | Bargetzi et al. | Mar 2017 | A1 |
| 20170078490 | Kaminsky et al. | Mar 2017 | A1 |
| 20170083179 | Gruber et al. | Mar 2017 | A1 |
| 20170083285 | Meyers et al. | Mar 2017 | A1 |
| 20170083504 | Huang | Mar 2017 | A1 |
| 20170083506 | Liu et al. | Mar 2017 | A1 |
| 20170084277 | Sharifi | Mar 2017 | A1 |
| 20170085547 | De Aguiar et al. | Mar 2017 | A1 |
| 20170085696 | Abkairov | Mar 2017 | A1 |
| 20170090428 | Oohara | Mar 2017 | A1 |
| 20170090569 | Levesque | Mar 2017 | A1 |
| 20170091168 | Bellegarda et al. | Mar 2017 | A1 |
| 20170091169 | Bellegarda et al. | Mar 2017 | A1 |
| 20170091612 | Gruber et al. | Mar 2017 | A1 |
| 20170092259 | Jeon | Mar 2017 | A1 |
| 20170092270 | Newendorp et al. | Mar 2017 | A1 |
| 20170092278 | Evermann et al. | Mar 2017 | A1 |
| 20170093356 | Cudak et al. | Mar 2017 | A1 |
| 20170097743 | Hameed et al. | Apr 2017 | A1 |
| 20170102837 | Toumpelis | Apr 2017 | A1 |
| 20170102915 | Kuscher et al. | Apr 2017 | A1 |
| 20170103749 | Zhao et al. | Apr 2017 | A1 |
| 20170103752 | Senior et al. | Apr 2017 | A1 |
| 20170105190 | Logan et al. | Apr 2017 | A1 |
| 20170108236 | Guan et al. | Apr 2017 | A1 |
| 20170110117 | Chakladar et al. | Apr 2017 | A1 |
| 20170110125 | Xu et al. | Apr 2017 | A1 |
| 20170116177 | Walia | Apr 2017 | A1 |
| 20170116982 | Gelfenbeyn et al. | Apr 2017 | A1 |
| 20170116987 | Kang et al. | Apr 2017 | A1 |
| 20170116989 | Yadgar et al. | Apr 2017 | A1 |
| 20170124190 | Wang et al. | May 2017 | A1 |
| 20170124311 | Li et al. | May 2017 | A1 |
| 20170124531 | McCormack | May 2017 | A1 |
| 20170125016 | Wang | May 2017 | A1 |
| 20170127124 | Wilson et al. | May 2017 | A9 |
| 20170131778 | Iyer | May 2017 | A1 |
| 20170132019 | Karashchuk et al. | May 2017 | A1 |
| 20170132199 | Vescovi et al. | May 2017 | A1 |
| 20170133007 | Drewes | May 2017 | A1 |
| 20170140041 | Dotan-Cohen et al. | May 2017 | A1 |
| 20170140052 | Bufe, III et al. | May 2017 | A1 |
| 20170140644 | Hwang et al. | May 2017 | A1 |
| 20170140760 | Sachdev | May 2017 | A1 |
| 20170147722 | Greenwood | May 2017 | A1 |
| 20170147841 | Stagg et al. | May 2017 | A1 |
| 20170148044 | Fukuda et al. | May 2017 | A1 |
| 20170154033 | Lee | Jun 2017 | A1 |
| 20170154055 | Dimson et al. | Jun 2017 | A1 |
| 20170154628 | Mohajer et al. | Jun 2017 | A1 |
| 20170155940 | Jin et al. | Jun 2017 | A1 |
| 20170155965 | Ward | Jun 2017 | A1 |
| 20170161018 | Lemay et al. | Jun 2017 | A1 |
| 20170161268 | Badaskar | Jun 2017 | A1 |
| 20170161293 | Ionescu et al. | Jun 2017 | A1 |
| 20170161393 | Oh et al. | Jun 2017 | A1 |
| 20170161439 | Raduchel et al. | Jun 2017 | A1 |
| 20170161500 | Yang | Jun 2017 | A1 |
| 20170162191 | Grost et al. | Jun 2017 | A1 |
| 20170162202 | Anthony et al. | Jun 2017 | A1 |
| 20170162203 | Huang et al. | Jun 2017 | A1 |
| 20170169506 | Wishne et al. | Jun 2017 | A1 |
| 20170169818 | Vanblon et al. | Jun 2017 | A1 |
| 20170169819 | Mese et al. | Jun 2017 | A1 |
| 20170171387 | Vendrow | Jun 2017 | A1 |
| 20170177080 | Deleeuw | Jun 2017 | A1 |
| 20170177547 | Ciereszko et al. | Jun 2017 | A1 |
| 20170178619 | Naik et al. | Jun 2017 | A1 |
| 20170178620 | Fleizach et al. | Jun 2017 | A1 |
| 20170178626 | Gruber et al. | Jun 2017 | A1 |
| 20170178666 | Yu | Jun 2017 | A1 |
| 20170180499 | Gelfenbeyn et al. | Jun 2017 | A1 |
| 20170185375 | Martel et al. | Jun 2017 | A1 |
| 20170185581 | Bojja et al. | Jun 2017 | A1 |
| 20170186429 | Giuli et al. | Jun 2017 | A1 |
| 20170187711 | Joo et al. | Jun 2017 | A1 |
| 20170193083 | Bhatt et al. | Jul 2017 | A1 |
| 20170195493 | Sudarsan et al. | Jul 2017 | A1 |
| 20170195495 | Deora et al. | Jul 2017 | A1 |
| 20170195636 | Child et al. | Jul 2017 | A1 |
| 20170195856 | Snyder et al. | Jul 2017 | A1 |
| 20170199870 | Zheng et al. | Jul 2017 | A1 |
| 20170199874 | Patel et al. | Jul 2017 | A1 |
| 20170200066 | Wang et al. | Jul 2017 | A1 |
| 20170201609 | Salmenkaita et al. | Jul 2017 | A1 |
| 20170201613 | Engelke et al. | Jul 2017 | A1 |
| 20170201846 | Katayama et al. | Jul 2017 | A1 |
| 20170206899 | Bryant et al. | Jul 2017 | A1 |
| 20170215052 | Koum et al. | Jul 2017 | A1 |
| 20170220212 | Yang et al. | Aug 2017 | A1 |
| 20170221486 | Kurata et al. | Aug 2017 | A1 |
| 20170223189 | Meredith et al. | Aug 2017 | A1 |
| 20170227935 | Su et al. | Aug 2017 | A1 |
| 20170228367 | Pasupalak et al. | Aug 2017 | A1 |
| 20170228382 | Haviv et al. | Aug 2017 | A1 |
| 20170229121 | Taki et al. | Aug 2017 | A1 |
| 20170230429 | Garmark et al. | Aug 2017 | A1 |
| 20170230497 | Kim et al. | Aug 2017 | A1 |
| 20170230709 | Van Os et al. | Aug 2017 | A1 |
| 20170235361 | Rigazio et al. | Aug 2017 | A1 |
| 20170235618 | Lin et al. | Aug 2017 | A1 |
| 20170235721 | Almosallam et al. | Aug 2017 | A1 |
| 20170236512 | Williams et al. | Aug 2017 | A1 |
| 20170236514 | Nelson | Aug 2017 | A1 |
| 20170236517 | Yu et al. | Aug 2017 | A1 |
| 20170238039 | Sabattini | Aug 2017 | A1 |
| 20170242478 | Ma | Aug 2017 | A1 |
| 20170242653 | Lang et al. | Aug 2017 | A1 |
| 20170242657 | Jarvis et al. | Aug 2017 | A1 |
| 20170242840 | Lu et al. | Aug 2017 | A1 |
| 20170243468 | Dotan-Cohen et al. | Aug 2017 | A1 |
| 20170243576 | Millington et al. | Aug 2017 | A1 |
| 20170243583 | Raichelgauz et al. | Aug 2017 | A1 |
| 20170243586 | Civelli et al. | Aug 2017 | A1 |
| 20170249309 | Sarikaya | Aug 2017 | A1 |
| 20170256256 | Wang et al. | Sep 2017 | A1 |
| 20170257723 | Morishita et al. | Sep 2017 | A1 |
| 20170262051 | Tall et al. | Sep 2017 | A1 |
| 20170263247 | Kang et al. | Sep 2017 | A1 |
| 20170263248 | Gruber et al. | Sep 2017 | A1 |
| 20170263249 | Akbacak et al. | Sep 2017 | A1 |
| 20170263254 | Dewan et al. | Sep 2017 | A1 |
| 20170264451 | Yu et al. | Sep 2017 | A1 |
| 20170264711 | Natarajan et al. | Sep 2017 | A1 |
| 20170270715 | Lindsay et al. | Sep 2017 | A1 |
| 20170270822 | Cohen | Sep 2017 | A1 |
| 20170270912 | Levit et al. | Sep 2017 | A1 |
| 20170273044 | Alsina | Sep 2017 | A1 |
| 20170278513 | Li et al. | Sep 2017 | A1 |
| 20170278514 | Mathias et al. | Sep 2017 | A1 |
| 20170285915 | Napolitano et al. | Oct 2017 | A1 |
| 20170286397 | Gonzalez | Oct 2017 | A1 |
| 20170286407 | Chochowski et al. | Oct 2017 | A1 |
| 20170287218 | Nuernberger et al. | Oct 2017 | A1 |
| 20170287472 | Ogawa et al. | Oct 2017 | A1 |
| 20170289305 | Liensberger et al. | Oct 2017 | A1 |
| 20170295446 | Shivappa | Oct 2017 | A1 |
| 20170301348 | Chen et al. | Oct 2017 | A1 |
| 20170308552 | Soni et al. | Oct 2017 | A1 |
| 20170308609 | Berkhin et al. | Oct 2017 | A1 |
| 20170311005 | Lin | Oct 2017 | A1 |
| 20170316775 | Le et al. | Nov 2017 | A1 |
| 20170316782 | Haughay | Nov 2017 | A1 |
| 20170319123 | Voss et al. | Nov 2017 | A1 |
| 20170323637 | Naik | Nov 2017 | A1 |
| 20170329466 | Krenkler et al. | Nov 2017 | A1 |
| 20170329490 | Esinovskaya et al. | Nov 2017 | A1 |
| 20170329572 | Shah et al. | Nov 2017 | A1 |
| 20170329630 | Jann et al. | Nov 2017 | A1 |
| 20170330567 | Van Wissen et al. | Nov 2017 | A1 |
| 20170336920 | Chan et al. | Nov 2017 | A1 |
| 20170337035 | Choudhary et al. | Nov 2017 | A1 |
| 20170337478 | Sarikaya et al. | Nov 2017 | A1 |
| 20170345411 | Raitio et al. | Nov 2017 | A1 |
| 20170345420 | Barnett, Jr. | Nov 2017 | A1 |
| 20170345429 | Hardee et al. | Nov 2017 | A1 |
| 20170346949 | Sanghavi et al. | Nov 2017 | A1 |
| 20170347180 | Petrank | Nov 2017 | A1 |
| 20170351487 | Avilés-Casco et al. | Dec 2017 | A1 |
| 20170352346 | Paulik et al. | Dec 2017 | A1 |
| 20170352350 | Booker et al. | Dec 2017 | A1 |
| 20170357478 | Piersol et al. | Dec 2017 | A1 |
| 20170357529 | Venkatraman et al. | Dec 2017 | A1 |
| 20170357632 | Pagallo et al. | Dec 2017 | A1 |
| 20170357633 | Wang et al. | Dec 2017 | A1 |
| 20170357637 | Nell et al. | Dec 2017 | A1 |
| 20170357640 | Bellegarda et al. | Dec 2017 | A1 |
| 20170357716 | Bellegarda et al. | Dec 2017 | A1 |
| 20170358300 | Laurens et al. | Dec 2017 | A1 |
| 20170358301 | Raitio et al. | Dec 2017 | A1 |
| 20170358302 | Orr et al. | Dec 2017 | A1 |
| 20170358303 | Walker, II et al. | Dec 2017 | A1 |
| 20170358304 | Castillo et al. | Dec 2017 | A1 |
| 20170358305 | Kudurshian et al. | Dec 2017 | A1 |
| 20170358317 | James | Dec 2017 | A1 |
| 20170359680 | Ledvina et al. | Dec 2017 | A1 |
| 20170365251 | Park et al. | Dec 2017 | A1 |
| 20170371509 | Jung et al. | Dec 2017 | A1 |
| 20170371885 | Aggarwal et al. | Dec 2017 | A1 |
| 20170374093 | Dhar et al. | Dec 2017 | A1 |
| 20170374176 | Agrawal et al. | Dec 2017 | A1 |
| 20180004372 | Zurek et al. | Jan 2018 | A1 |
| 20180004396 | Mng | Jan 2018 | A1 |
| 20180005112 | Iso-Sipila et al. | Jan 2018 | A1 |
| 20180007060 | Leblang et al. | Jan 2018 | A1 |
| 20180007096 | Levin et al. | Jan 2018 | A1 |
| 20180007538 | Naik et al. | Jan 2018 | A1 |
| 20180012596 | Piernot et al. | Jan 2018 | A1 |
| 20180018248 | Bhargava et al. | Jan 2018 | A1 |
| 20180018590 | Szeto et al. | Jan 2018 | A1 |
| 20180018814 | Patrik et al. | Jan 2018 | A1 |
| 20180018959 | Des Jardins et al. | Jan 2018 | A1 |
| 20180018973 | Moreno et al. | Jan 2018 | A1 |
| 20180020093 | Bentitou et al. | Jan 2018 | A1 |
| 20180024985 | Asano | Jan 2018 | A1 |
| 20180025124 | Mohr et al. | Jan 2018 | A1 |
| 20180025287 | Mathew et al. | Jan 2018 | A1 |
| 20180028918 | Tang et al. | Feb 2018 | A1 |
| 20180033431 | Newendorp et al. | Feb 2018 | A1 |
| 20180033435 | Jacobs, II | Feb 2018 | A1 |
| 20180033436 | Zhou | Feb 2018 | A1 |
| 20180045963 | Hoover et al. | Feb 2018 | A1 |
| 20180046340 | Mall | Feb 2018 | A1 |
| 20180047201 | Filev et al. | Feb 2018 | A1 |
| 20180047391 | Baik et al. | Feb 2018 | A1 |
| 20180047393 | Tian et al. | Feb 2018 | A1 |
| 20180047406 | Park | Feb 2018 | A1 |
| 20180052909 | Sharifi et al. | Feb 2018 | A1 |
| 20180054505 | Hart et al. | Feb 2018 | A1 |
| 20180060032 | Boesen | Mar 2018 | A1 |
| 20180060301 | Li et al. | Mar 2018 | A1 |
| 20180060312 | Won | Mar 2018 | A1 |
| 20180060555 | Boesen | Mar 2018 | A1 |
| 20180061400 | Carbune et al. | Mar 2018 | A1 |
| 20180061401 | Sarikaya et al. | Mar 2018 | A1 |
| 20180062691 | Barnett, Jr. | Mar 2018 | A1 |
| 20180063308 | Crystal et al. | Mar 2018 | A1 |
| 20180063324 | Van Meter, II | Mar 2018 | A1 |
| 20180063624 | Boesen | Mar 2018 | A1 |
| 20180067904 | Li | Mar 2018 | A1 |
| 20180067914 | Chen et al. | Mar 2018 | A1 |
| 20180067918 | Bellegarda et al. | Mar 2018 | A1 |
| 20180067929 | Ahn | Mar 2018 | A1 |
| 20180068074 | Shen | Mar 2018 | A1 |
| 20180068194 | Matsuda | Mar 2018 | A1 |
| 20180069743 | Bakken et al. | Mar 2018 | A1 |
| 20180075847 | Lee et al. | Mar 2018 | A1 |
| 20180075849 | Khoury et al. | Mar 2018 | A1 |
| 20180077095 | Deyle et al. | Mar 2018 | A1 |
| 20180077648 | Nguyen | Mar 2018 | A1 |
| 20180082692 | Khoury et al. | Mar 2018 | A1 |
| 20180088788 | Cheung et al. | Mar 2018 | A1 |
| 20180088969 | Vanblon et al. | Mar 2018 | A1 |
| 20180089166 | Meyer et al. | Mar 2018 | A1 |
| 20180089588 | Ravi et al. | Mar 2018 | A1 |
| 20180090143 | Saddler et al. | Mar 2018 | A1 |
| 20180091604 | Yamashita et al. | Mar 2018 | A1 |
| 20180091732 | Wilson et al. | Mar 2018 | A1 |
| 20180091847 | Wu et al. | Mar 2018 | A1 |
| 20180096683 | James et al. | Apr 2018 | A1 |
| 20180096690 | Mixter et al. | Apr 2018 | A1 |
| 20180101599 | Kenneth et al. | Apr 2018 | A1 |
| 20180101925 | Brinig et al. | Apr 2018 | A1 |
| 20180102914 | Kawachi et al. | Apr 2018 | A1 |
| 20180103209 | Fischler et al. | Apr 2018 | A1 |
| 20180107917 | Hewavitharana et al. | Apr 2018 | A1 |
| 20180107945 | Gao et al. | Apr 2018 | A1 |
| 20180108346 | Paulik et al. | Apr 2018 | A1 |
| 20180108351 | Beckhardt et al. | Apr 2018 | A1 |
| 20180108357 | Liu | Apr 2018 | A1 |
| 20180109920 | Aggarwal et al. | Apr 2018 | A1 |
| 20180113673 | Sheynblat | Apr 2018 | A1 |
| 20180314362 | Kim et al. | Apr 2018 | A1 |
| 20180121430 | Kagoshima et al. | May 2018 | A1 |
| 20180121432 | Parson et al. | May 2018 | A1 |
| 20180122376 | Kojima | May 2018 | A1 |
| 20180122378 | Mixter et al. | May 2018 | A1 |
| 20180126260 | Chansoriya et al. | May 2018 | A1 |
| 20180129967 | Herreshoff | May 2018 | A1 |
| 20180130470 | Lemay et al. | May 2018 | A1 |
| 20180130471 | Trufinescu et al. | May 2018 | A1 |
| 20180137856 | Gilbert | May 2018 | A1 |
| 20180137857 | Zhou et al. | May 2018 | A1 |
| 20180137865 | Ling | May 2018 | A1 |
| 20180143857 | Anbazhagan et al. | May 2018 | A1 |
| 20180143967 | Anbazhagan et al. | May 2018 | A1 |
| 20180144465 | Hsieh et al. | May 2018 | A1 |
| 20180144615 | Kinney et al. | May 2018 | A1 |
| 20180144746 | Mishra et al. | May 2018 | A1 |
| 20180144748 | Leong | May 2018 | A1 |
| 20180146089 | Rauenbuehler et al. | May 2018 | A1 |
| 20180150744 | Orr et al. | May 2018 | A1 |
| 20180152557 | White et al. | May 2018 | A1 |
| 20180152558 | Chan et al. | May 2018 | A1 |
| 20180152803 | Seefeldt et al. | May 2018 | A1 |
| 20180157372 | Kurabayashi | Jun 2018 | A1 |
| 20180157408 | Yu et al. | Jun 2018 | A1 |
| 20180157992 | Susskind et al. | Jun 2018 | A1 |
| 20180158548 | Taheri et al. | Jun 2018 | A1 |
| 20180158552 | Liu et al. | Jun 2018 | A1 |
| 20180165857 | Lee et al. | Jun 2018 | A1 |
| 20180166076 | Higuchi et al. | Jun 2018 | A1 |
| 20180167884 | Dawid et al. | Jun 2018 | A1 |
| 20180173403 | Carbune et al. | Jun 2018 | A1 |
| 20180173542 | Chan et al. | Jun 2018 | A1 |
| 20180174406 | Arashi et al. | Jun 2018 | A1 |
| 20180174576 | Soltau et al. | Jun 2018 | A1 |
| 20180174597 | Lee et al. | Jun 2018 | A1 |
| 20180181370 | Parkinson | Jun 2018 | A1 |
| 20180182376 | Gysel et al. | Jun 2018 | A1 |
| 20180188840 | Tamura et al. | Jul 2018 | A1 |
| 20180188948 | Ouyang et al. | Jul 2018 | A1 |
| 20180189267 | Takiel | Jul 2018 | A1 |
| 20180190263 | Calef, III | Jul 2018 | A1 |
| 20180190273 | Karimli et al. | Jul 2018 | A1 |
| 20180190279 | Anderson et al. | Jul 2018 | A1 |
| 20180191670 | Suyama | Jul 2018 | A1 |
| 20180196683 | Radebaugh et al. | Jul 2018 | A1 |
| 20180205983 | Lee et al. | Jul 2018 | A1 |
| 20180210874 | Fuxman et al. | Jul 2018 | A1 |
| 20180213448 | Segal et al. | Jul 2018 | A1 |
| 20180214061 | Knoth et al. | Aug 2018 | A1 |
| 20180217810 | Agrawal | Aug 2018 | A1 |
| 20180218735 | Hunt et al. | Aug 2018 | A1 |
| 20180221783 | Gamero | Aug 2018 | A1 |
| 20180225131 | Tommy et al. | Aug 2018 | A1 |
| 20180225274 | Tommy et al. | Aug 2018 | A1 |
| 20180232203 | Gelfenbeyn et al. | Aug 2018 | A1 |
| 20180232608 | Pradeep et al. | Aug 2018 | A1 |
| 20180232688 | Pike et al. | Aug 2018 | A1 |
| 20180233132 | Herold et al. | Aug 2018 | A1 |
| 20180233140 | Koishida et al. | Aug 2018 | A1 |
| 20180247065 | Rhee et al. | Aug 2018 | A1 |
| 20180253209 | Jaygarl et al. | Sep 2018 | A1 |
| 20180253652 | Palzer et al. | Sep 2018 | A1 |
| 20180260680 | Finkelstein et al. | Sep 2018 | A1 |
| 20180268023 | Korpusik et al. | Sep 2018 | A1 |
| 20180268106 | Velaga | Sep 2018 | A1 |
| 20180268337 | Miller et al. | Sep 2018 | A1 |
| 20180270343 | Rout et al. | Sep 2018 | A1 |
| 20180275839 | Kocienda et al. | Sep 2018 | A1 |
| 20180276197 | Nell et al. | Sep 2018 | A1 |
| 20180277113 | Hartung et al. | Sep 2018 | A1 |
| 20180278740 | Choi et al. | Sep 2018 | A1 |
| 20180285056 | Cutler et al. | Oct 2018 | A1 |
| 20180293984 | Lindahl | Oct 2018 | A1 |
| 20180293988 | Huang et al. | Oct 2018 | A1 |
| 20180293989 | De et al. | Oct 2018 | A1 |
| 20180299878 | Cella et al. | Oct 2018 | A1 |
| 20180300317 | Bradbury | Oct 2018 | A1 |
| 20180300400 | Paulus | Oct 2018 | A1 |
| 20180300608 | Sevrens et al. | Oct 2018 | A1 |
| 20180300952 | Evans et al. | Oct 2018 | A1 |
| 20180307216 | Ypma et al. | Oct 2018 | A1 |
| 20180308470 | Park et al. | Oct 2018 | A1 |
| 20180308477 | Nagasaka | Oct 2018 | A1 |
| 20180308480 | Jang et al. | Oct 2018 | A1 |
| 20180308485 | Kudurshian et al. | Oct 2018 | A1 |
| 20180308486 | Saddler et al. | Oct 2018 | A1 |
| 20180308491 | Oktem et al. | Oct 2018 | A1 |
| 20180314552 | Kim et al. | Nov 2018 | A1 |
| 20180314689 | Wang et al. | Nov 2018 | A1 |
| 20180315415 | Mosley et al. | Nov 2018 | A1 |
| 20180315416 | Berthelsen et al. | Nov 2018 | A1 |
| 20180322112 | Bellegarda et al. | Nov 2018 | A1 |
| 20180322881 | Min et al. | Nov 2018 | A1 |
| 20180324518 | Dusan et al. | Nov 2018 | A1 |
| 20180329508 | Klein et al. | Nov 2018 | A1 |
| 20180329677 | Gruber et al. | Nov 2018 | A1 |
| 20180329957 | Frazzingaro et al. | Nov 2018 | A1 |
| 20180329982 | Patel et al. | Nov 2018 | A1 |
| 20180329998 | Thomson et al. | Nov 2018 | A1 |
| 20180330714 | Paulik et al. | Nov 2018 | A1 |
| 20180330721 | Thomson et al. | Nov 2018 | A1 |
| 20180330722 | Newendorp et al. | Nov 2018 | A1 |
| 20180330723 | Acero et al. | Nov 2018 | A1 |
| 20180330729 | Golipour et al. | Nov 2018 | A1 |
| 20180330730 | Garg et al. | Nov 2018 | A1 |
| 20180330731 | Zeitlin et al. | Nov 2018 | A1 |
| 20180330733 | Orr et al. | Nov 2018 | A1 |
| 20180330737 | Paulik et al. | Nov 2018 | A1 |
| 20180332118 | Phipps et al. | Nov 2018 | A1 |
| 20180332389 | Ekkizogloy et al. | Nov 2018 | A1 |
| 20180335903 | Coffman et al. | Nov 2018 | A1 |
| 20180336006 | Chakraborty et al. | Nov 2018 | A1 |
| 20180336049 | Mukherjee et al. | Nov 2018 | A1 |
| 20180336184 | Bellegarda et al. | Nov 2018 | A1 |
| 20180336197 | Skilling et al. | Nov 2018 | A1 |
| 20180336275 | Graham et al. | Nov 2018 | A1 |
| 20180336439 | Kliger et al. | Nov 2018 | A1 |
| 20180336449 | Adan et al. | Nov 2018 | A1 |
| 20180336880 | Arik et al. | Nov 2018 | A1 |
| 20180336885 | Mukherjee et al. | Nov 2018 | A1 |
| 20180336892 | Kim et al. | Nov 2018 | A1 |
| 20180336894 | Graham et al. | Nov 2018 | A1 |
| 20180336904 | Piercy et al. | Nov 2018 | A1 |
| 20180336905 | Kim et al. | Nov 2018 | A1 |
| 20180336911 | Dahl et al. | Nov 2018 | A1 |
| 20180336920 | Bastian et al. | Nov 2018 | A1 |
| 20180338191 | Van Scheltinga et al. | Nov 2018 | A1 |
| 20180341643 | Alders et al. | Nov 2018 | A1 |
| 20180343557 | Naik et al. | Nov 2018 | A1 |
| 20180349084 | Nagasaka et al. | Dec 2018 | A1 |
| 20180349346 | Hatori et al. | Dec 2018 | A1 |
| 20180349349 | Bellegarda et al. | Dec 2018 | A1 |
| 20180349447 | Maccartney et al. | Dec 2018 | A1 |
| 20180349472 | Kohlschuetter et al. | Dec 2018 | A1 |
| 20180349728 | Wang et al. | Dec 2018 | A1 |
| 20180350345 | Naik | Dec 2018 | A1 |
| 20180350353 | Gruber et al. | Dec 2018 | A1 |
| 20180357073 | Johnson et al. | Dec 2018 | A1 |
| 20180357308 | Cheyer | Dec 2018 | A1 |
| 20180358015 | Cash et al. | Dec 2018 | A1 |
| 20180358019 | Mont-Reynaud | Dec 2018 | A1 |
| 20180365653 | Cleaver et al. | Dec 2018 | A1 |
| 20180366105 | Kim | Dec 2018 | A1 |
| 20180366110 | Hashem et al. | Dec 2018 | A1 |
| 20180366116 | Nicholson et al. | Dec 2018 | A1 |
| 20180373487 | Gruber et al. | Dec 2018 | A1 |
| 20180373493 | Watson et al. | Dec 2018 | A1 |
| 20180373796 | Rathod | Dec 2018 | A1 |
| 20180374484 | Huang et al. | Dec 2018 | A1 |
| 20190005024 | Somech et al. | Jan 2019 | A1 |
| 20190012141 | Piersol et al. | Jan 2019 | A1 |
| 20190012445 | Lesso et al. | Jan 2019 | A1 |
| 20190012449 | Cheyer | Jan 2019 | A1 |
| 20190012599 | El Kaliouby et al. | Jan 2019 | A1 |
| 20190013018 | Rekstad | Jan 2019 | A1 |
| 20190013025 | Alcorn et al. | Jan 2019 | A1 |
| 20190014450 | Gruber et al. | Jan 2019 | A1 |
| 20190019077 | Griffin et al. | Jan 2019 | A1 |
| 20190020482 | Gupta et al. | Jan 2019 | A1 |
| 20190027152 | Huang et al. | Jan 2019 | A1 |
| 20190034040 | Shah et al. | Jan 2019 | A1 |
| 20190034826 | Ahmad et al. | Jan 2019 | A1 |
| 20190035385 | Lawson et al. | Jan 2019 | A1 |
| 20190035405 | Haughay | Jan 2019 | A1 |
| 20190037258 | Justin et al. | Jan 2019 | A1 |
| 20190042059 | Baer | Feb 2019 | A1 |
| 20190042627 | Osotio et al. | Feb 2019 | A1 |
| 20190043507 | Huang et al. | Feb 2019 | A1 |
| 20190044854 | Yang et al. | Feb 2019 | A1 |
| 20190045040 | Lee et al. | Feb 2019 | A1 |
| 20190051306 | Torama et al. | Feb 2019 | A1 |
| 20190051309 | Kim et al. | Feb 2019 | A1 |
| 20190057697 | Giuli et al. | Feb 2019 | A1 |
| 20190065144 | Sumner et al. | Feb 2019 | A1 |
| 20190065993 | Srinivasan et al. | Feb 2019 | A1 |
| 20190066674 | Jaygarl et al. | Feb 2019 | A1 |
| 20190068810 | Okamoto et al. | Feb 2019 | A1 |
| 20190173996 | Butcher et al. | Feb 2019 | A1 |
| 20190073607 | Jia et al. | Mar 2019 | A1 |
| 20190073998 | Leblang et al. | Mar 2019 | A1 |
| 20190074009 | Kim et al. | Mar 2019 | A1 |
| 20190074015 | Orr et al. | Mar 2019 | A1 |
| 20190074016 | Orr et al. | Mar 2019 | A1 |
| 20190079476 | Funes | Mar 2019 | A1 |
| 20190079724 | Feuz et al. | Mar 2019 | A1 |
| 20190080685 | Johnson, Jr. | Mar 2019 | A1 |
| 20190080698 | Miller | Mar 2019 | A1 |
| 20190082044 | Olivia et al. | Mar 2019 | A1 |
| 20190087412 | Seyed Ibrahim et al. | Mar 2019 | A1 |
| 20190087455 | He et al. | Mar 2019 | A1 |
| 20190095050 | Gruber et al. | Mar 2019 | A1 |
| 20190095069 | Proctor et al. | Mar 2019 | A1 |
| 20190095171 | Carson et al. | Mar 2019 | A1 |
| 20190102145 | Wilberding et al. | Apr 2019 | A1 |
| 20190102378 | Piernot et al. | Apr 2019 | A1 |
| 20190102381 | Futrell et al. | Apr 2019 | A1 |
| 20190103103 | Ni et al. | Apr 2019 | A1 |
| 20190103112 | Walker et al. | Apr 2019 | A1 |
| 20190108834 | Nelson et al. | Apr 2019 | A1 |
| 20190114320 | Patwardhan et al. | Apr 2019 | A1 |
| 20190116264 | Sanghavi et al. | Apr 2019 | A1 |
| 20190122666 | Raitio et al. | Apr 2019 | A1 |
| 20190122692 | Binder et al. | Apr 2019 | A1 |
| 20190124019 | Leon et al. | Apr 2019 | A1 |
| 20190129499 | Li | May 2019 | A1 |
| 20190129615 | Sundar et al. | May 2019 | A1 |
| 20190132694 | Hanes et al. | May 2019 | A1 |
| 20190134501 | Feder et al. | May 2019 | A1 |
| 20190138704 | Shrivastava et al. | May 2019 | A1 |
| 20190139541 | Andersen et al. | May 2019 | A1 |
| 20190139563 | Chen et al. | May 2019 | A1 |
| 20190141494 | Gross et al. | May 2019 | A1 |
| 20190147052 | Lu et al. | May 2019 | A1 |
| 20190147369 | Gupta et al. | May 2019 | A1 |
| 20190147880 | Booker et al. | May 2019 | A1 |
| 20190147883 | Mellenthin et al. | May 2019 | A1 |
| 20190149972 | Parks et al. | May 2019 | A1 |
| 20190156830 | Devaraj et al. | May 2019 | A1 |
| 20190158994 | Gross et al. | May 2019 | A1 |
| 20190163667 | Feuz et al. | May 2019 | A1 |
| 20190164546 | Piernot et al. | May 2019 | A1 |
| 20190172243 | Mishra et al. | Jun 2019 | A1 |
| 20190172458 | Mishra et al. | Jun 2019 | A1 |
| 20190172467 | Kim et al. | Jun 2019 | A1 |
| 20190179607 | Thangarathnam et al. | Jun 2019 | A1 |
| 20190179890 | Evermann | Jun 2019 | A1 |
| 20190180770 | Kothari et al. | Jun 2019 | A1 |
| 20190182176 | Niewczas | Jun 2019 | A1 |
| 20190187787 | White et al. | Jun 2019 | A1 |
| 20190188326 | Daianu et al. | Jun 2019 | A1 |
| 20190188328 | Oyenan et al. | Jun 2019 | A1 |
| 20190189118 | Piernot et al. | Jun 2019 | A1 |
| 20190189125 | Van Os et al. | Jun 2019 | A1 |
| 20190190898 | Cui | Jun 2019 | A1 |
| 20190197053 | Graham et al. | Jun 2019 | A1 |
| 20190213498 | Adjaoute | Jul 2019 | A1 |
| 20190213601 | Hackman et al. | Jul 2019 | A1 |
| 20190213774 | Jiao et al. | Jul 2019 | A1 |
| 20190213999 | Grupen et al. | Jul 2019 | A1 |
| 20190214024 | Gruber et al. | Jul 2019 | A1 |
| 20190220245 | Martel et al. | Jul 2019 | A1 |
| 20190220246 | Orr et al. | Jul 2019 | A1 |
| 20190220247 | Lemay et al. | Jul 2019 | A1 |
| 20190220704 | Schulz-Trieglaff et al. | Jul 2019 | A1 |
| 20190220727 | Dohrmann et al. | Jul 2019 | A1 |
| 20190222684 | Li et al. | Jul 2019 | A1 |
| 20190224049 | Creasy et al. | Jul 2019 | A1 |
| 20190230215 | Zhu et al. | Jul 2019 | A1 |
| 20190230426 | Chun | Jul 2019 | A1 |
| 20190236130 | Li et al. | Aug 2019 | A1 |
| 20190236459 | Cheyer et al. | Aug 2019 | A1 |
| 20190237061 | Rusak et al. | Aug 2019 | A1 |
| 20190243902 | Saeki et al. | Aug 2019 | A1 |
| 20190244618 | Newendorp et al. | Aug 2019 | A1 |
| 20190251167 | Krishnapura Subbaraya et al. | Aug 2019 | A1 |
| 20190251339 | Hawker | Aug 2019 | A1 |
| 20190251960 | Maker et al. | Aug 2019 | A1 |
| 20190259386 | Kudurshian et al. | Aug 2019 | A1 |
| 20190266246 | Wang et al. | Aug 2019 | A1 |
| 20190272318 | Suzuki et al. | Sep 2019 | A1 |
| 20190272818 | Fernandez et al. | Sep 2019 | A1 |
| 20190272825 | O'Malley et al. | Sep 2019 | A1 |
| 20190272831 | Kajarekar | Sep 2019 | A1 |
| 20190273963 | Jobanputra et al. | Sep 2019 | A1 |
| 20190278841 | Pusateri et al. | Sep 2019 | A1 |
| 20190279622 | Liu et al. | Sep 2019 | A1 |
| 20190281387 | Woo et al. | Sep 2019 | A1 |
| 20190287012 | Asli et al. | Sep 2019 | A1 |
| 20190287522 | Lambourne et al. | Sep 2019 | A1 |
| 20190294769 | Lesso | Sep 2019 | A1 |
| 20190294962 | Vezer et al. | Sep 2019 | A1 |
| 20190295529 | Tomita | Sep 2019 | A1 |
| 20190295540 | Grima | Sep 2019 | A1 |
| 20190295544 | Garcia et al. | Sep 2019 | A1 |
| 20190303442 | Peitz et al. | Oct 2019 | A1 |
| 20190303504 | Pasumarthy | Oct 2019 | A1 |
| 20190304438 | Qian et al. | Oct 2019 | A1 |
| 20190310765 | Napolitano et al. | Oct 2019 | A1 |
| 20190311708 | Bengio et al. | Oct 2019 | A1 |
| 20190311720 | Pasko | Oct 2019 | A1 |
| 20190318722 | Bromand | Oct 2019 | A1 |
| 20190318724 | Chao et al. | Oct 2019 | A1 |
| 20190318725 | Le Roux et al. | Oct 2019 | A1 |
| 20190318732 | Huang et al. | Oct 2019 | A1 |
| 20190318735 | Chao et al. | Oct 2019 | A1 |
| 20190318739 | Garg et al. | Oct 2019 | A1 |
| 20190325866 | Bromand et al. | Oct 2019 | A1 |
| 20190333523 | Kim et al. | Oct 2019 | A1 |
| 20190339784 | Lemay et al. | Nov 2019 | A1 |
| 20190340252 | Huyghe | Nov 2019 | A1 |
| 20190341027 | Vescovi et al. | Nov 2019 | A1 |
| 20190341056 | Paulik et al. | Nov 2019 | A1 |
| 20190347063 | Liu et al. | Nov 2019 | A1 |
| 20190347525 | Liem et al. | Nov 2019 | A1 |
| 20190348022 | Park et al. | Nov 2019 | A1 |
| 20190349333 | Pickover et al. | Nov 2019 | A1 |
| 20190349622 | Kim et al. | Nov 2019 | A1 |
| 20190354548 | Orr et al. | Nov 2019 | A1 |
| 20190355346 | Bellegarda | Nov 2019 | A1 |
| 20190355384 | Sereshki et al. | Nov 2019 | A1 |
| 20190361729 | Gruber et al. | Nov 2019 | A1 |
| 20190361978 | Ray et al. | Nov 2019 | A1 |
| 20190362557 | Lacey et al. | Nov 2019 | A1 |
| 20190369748 | Hindi et al. | Dec 2019 | A1 |
| 20190369842 | Dolbakian et al. | Dec 2019 | A1 |
| 20190369868 | Jin et al. | Dec 2019 | A1 |
| 20190370292 | Irani et al. | Dec 2019 | A1 |
| 20190370323 | Davidson et al. | Dec 2019 | A1 |
| 20190370443 | Lesso | Dec 2019 | A1 |
| 20190371315 | Newendorp et al. | Dec 2019 | A1 |
| 20190371316 | Weinstein et al. | Dec 2019 | A1 |
| 20190371317 | Irani et al. | Dec 2019 | A1 |
| 20190371331 | Schramm et al. | Dec 2019 | A1 |
| 20190372902 | Piersol | Dec 2019 | A1 |
| 20190373102 | Weinstein et al. | Dec 2019 | A1 |
| 20190377955 | Swaminathan et al. | Dec 2019 | A1 |
| 20190385418 | Mixter et al. | Dec 2019 | A1 |
| 20190387352 | Jot et al. | Dec 2019 | A1 |
| 20200019609 | Yu et al. | Jan 2020 | A1 |
| 20200020326 | Srinivasan et al. | Jan 2020 | A1 |
| 20200034421 | Ferrucci et al. | Jan 2020 | A1 |
| 20200035224 | Ward et al. | Jan 2020 | A1 |
| 20200042334 | Radebaugh et al. | Feb 2020 | A1 |
| 20200043467 | Qian et al. | Feb 2020 | A1 |
| 20200043471 | Ma et al. | Feb 2020 | A1 |
| 20200043482 | Gruber et al. | Feb 2020 | A1 |
| 20200043489 | Bradley et al. | Feb 2020 | A1 |
| 20200044485 | Smith et al. | Feb 2020 | A1 |
| 20200051565 | Singh | Feb 2020 | A1 |
| 20200051583 | Wu et al. | Feb 2020 | A1 |
| 20200053218 | Gray | Feb 2020 | A1 |
| 20200058299 | Lee et al. | Feb 2020 | A1 |
| 20200065601 | Andreassen | Feb 2020 | A1 |
| 20200073629 | Lee et al. | Mar 2020 | A1 |
| 20200075018 | Chen | Mar 2020 | A1 |
| 20200075040 | Provost et al. | Mar 2020 | A1 |
| 20200076538 | Soultan et al. | Mar 2020 | A1 |
| 20200081615 | et al. | Mar 2020 | A1 |
| 20200082807 | Kim et al. | Mar 2020 | A1 |
| 20200084572 | Jadav et al. | Mar 2020 | A1 |
| 20200090393 | Shin et al. | Mar 2020 | A1 |
| 20200091958 | Curtis et al. | Mar 2020 | A1 |
| 20200092625 | Raffle | Mar 2020 | A1 |
| 20200098352 | Feinstein et al. | Mar 2020 | A1 |
| 20200098362 | Piernot et al. | Mar 2020 | A1 |
| 20200098368 | Lemay et al. | Mar 2020 | A1 |
| 20200103963 | Kelly et al. | Apr 2020 | A1 |
| 20200104357 | Bellegarda et al. | Apr 2020 | A1 |
| 20200104362 | Yang et al. | Apr 2020 | A1 |
| 20200104369 | Bellegarda | Apr 2020 | A1 |
| 20200104668 | Sanghavi et al. | Apr 2020 | A1 |
| 20200105260 | Piernot et al. | Apr 2020 | A1 |
| 20200112454 | Brown et al. | Apr 2020 | A1 |
| 20200117717 | Ramamurti et al. | Apr 2020 | A1 |
| 20200118566 | Zhou | Apr 2020 | A1 |
| 20200118568 | Kudurshian et al. | Apr 2020 | A1 |
| 20200125820 | Kim et al. | Apr 2020 | A1 |
| 20200127988 | Bradley et al. | Apr 2020 | A1 |
| 20200134316 | Krishnamurthy et al. | Apr 2020 | A1 |
| 20200135180 | Mukherjee et al. | Apr 2020 | A1 |
| 20200135209 | Delfarah et al. | Apr 2020 | A1 |
| 20200135226 | Mittal et al. | Apr 2020 | A1 |
| 20200137230 | Spohrer | Apr 2020 | A1 |
| 20200143812 | Walker, II et al. | May 2020 | A1 |
| 20200143819 | Delcroix et al. | May 2020 | A1 |
| 20200152186 | Koh et al. | May 2020 | A1 |
| 20200159579 | Shear et al. | May 2020 | A1 |
| 20200159651 | Myers | May 2020 | A1 |
| 20200159801 | Sekine | May 2020 | A1 |
| 20200160179 | Chien et al. | May 2020 | A1 |
| 20200160838 | Lee | May 2020 | A1 |
| 20200168120 | Rodriguez Bravo | May 2020 | A1 |
| 20200169637 | Sanghavi et al. | May 2020 | A1 |
| 20200175566 | Bender et al. | Jun 2020 | A1 |
| 20200176004 | Kleijn et al. | Jun 2020 | A1 |
| 20200176018 | Feinauer et al. | Jun 2020 | A1 |
| 20200184057 | Mukund | Jun 2020 | A1 |
| 20200184964 | Myers et al. | Jun 2020 | A1 |
| 20200184966 | Yavagal | Jun 2020 | A1 |
| 20200193997 | Piernot et al. | Jun 2020 | A1 |
| 20200210142 | Mu et al. | Jul 2020 | A1 |
| 20200211566 | Kang et al. | Jul 2020 | A1 |
| 20200218074 | Hoover et al. | Jul 2020 | A1 |
| 20200218780 | Jun et al. | Jul 2020 | A1 |
| 20200219517 | Wang et al. | Jul 2020 | A1 |
| 20200221155 | Hansen et al. | Jul 2020 | A1 |
| 20200226823 | Stachniak et al. | Jul 2020 | A1 |
| 20200227034 | Summa et al. | Jul 2020 | A1 |
| 20200227044 | Lindahl | Jul 2020 | A1 |
| 20200228774 | Kar et al. | Jul 2020 | A1 |
| 20200243069 | Amores et al. | Jul 2020 | A1 |
| 20200243094 | Thomson et al. | Jul 2020 | A1 |
| 20200249985 | Zeitlin | Aug 2020 | A1 |
| 20200252508 | Gray | Aug 2020 | A1 |
| 20200258508 | Aggarwal et al. | Aug 2020 | A1 |
| 20200267222 | Phipps et al. | Aug 2020 | A1 |
| 20200272485 | Karashchuk et al. | Aug 2020 | A1 |
| 20200279556 | Gruber et al. | Sep 2020 | A1 |
| 20200279576 | Binder et al. | Sep 2020 | A1 |
| 20200279627 | Nida et al. | Sep 2020 | A1 |
| 20200285327 | Hindi et al. | Sep 2020 | A1 |
| 20200286472 | Newendorp et al. | Sep 2020 | A1 |
| 20200286493 | Orr et al. | Sep 2020 | A1 |
| 20200294487 | Donohoe et al. | Sep 2020 | A1 |
| 20200294494 | Suyama et al. | Sep 2020 | A1 |
| 20200298394 | Han et al. | Sep 2020 | A1 |
| 20200301950 | Theo et al. | Sep 2020 | A1 |
| 20200302356 | Gruber et al. | Sep 2020 | A1 |
| 20200302919 | Greborio et al. | Sep 2020 | A1 |
| 20200302925 | Shah et al. | Sep 2020 | A1 |
| 20200302930 | Chen et al. | Sep 2020 | A1 |
| 20200302932 | Schramm et al. | Sep 2020 | A1 |
| 20200304955 | Gross et al. | Sep 2020 | A1 |
| 20200304972 | Gross et al. | Sep 2020 | A1 |
| 20200305084 | Freeman et al. | Sep 2020 | A1 |
| 20200310513 | Nicholson et al. | Oct 2020 | A1 |
| 20200312315 | Li et al. | Oct 2020 | A1 |
| 20200312317 | Kothari et al. | Oct 2020 | A1 |
| 20200314191 | Madhavan et al. | Oct 2020 | A1 |
| 20200319850 | Stasior et al. | Oct 2020 | A1 |
| 20200320592 | Soule et al. | Oct 2020 | A1 |
| 20200327895 | Gruber et al. | Oct 2020 | A1 |
| 20200333875 | Bansal et al. | Oct 2020 | A1 |
| 20200334492 | Zheng et al. | Oct 2020 | A1 |
| 20200335121 | Mosseri et al. | Oct 2020 | A1 |
| 20200342082 | Sapozhnykov et al. | Oct 2020 | A1 |
| 20200342849 | Yu et al. | Oct 2020 | A1 |
| 20200342863 | Aggarwal et al. | Oct 2020 | A1 |
| 20200356243 | Meyer et al. | Nov 2020 | A1 |
| 20200356589 | Rekik et al. | Nov 2020 | A1 |
| 20200356634 | Srinivasan et al. | Nov 2020 | A1 |
| 20200357391 | Ghoshal et al. | Nov 2020 | A1 |
| 20200357406 | York et al. | Nov 2020 | A1 |
| 20200357409 | Sun et al. | Nov 2020 | A1 |
| 20200364411 | Evermann | Nov 2020 | A1 |
| 20200364858 | Kaethner et al. | Nov 2020 | A1 |
| 20200365155 | Milden | Nov 2020 | A1 |
| 20200367006 | Beckhardt | Nov 2020 | A1 |
| 20200372633 | Lee, II et al. | Nov 2020 | A1 |
| 20200372904 | Vescovi et al. | Nov 2020 | A1 |
| 20200372905 | Wang et al. | Nov 2020 | A1 |
| 20200374243 | Jina et al. | Nov 2020 | A1 |
| 20200379610 | Ford et al. | Dec 2020 | A1 |
| 20200379640 | Bellegarda et al. | Dec 2020 | A1 |
| 20200379726 | Blatz et al. | Dec 2020 | A1 |
| 20200379727 | Blatz et al. | Dec 2020 | A1 |
| 20200379728 | Gada et al. | Dec 2020 | A1 |
| 20200380389 | Eldeeb et al. | Dec 2020 | A1 |
| 20200380956 | Rossi et al. | Dec 2020 | A1 |
| 20200380963 | Chappidi et al. | Dec 2020 | A1 |
| 20200380966 | Acero et al. | Dec 2020 | A1 |
| 20200380973 | Novitchenko et al. | Dec 2020 | A1 |
| 20200380980 | Shum et al. | Dec 2020 | A1 |
| 20200380985 | Gada et al. | Dec 2020 | A1 |
| 20200382616 | Vaishampayan et al. | Dec 2020 | A1 |
| 20200382635 | Vora et al. | Dec 2020 | A1 |
| 20210006943 | Gross et al. | Jan 2021 | A1 |
| 20210011557 | Lemay et al. | Jan 2021 | A1 |
| 20210012113 | Petill et al. | Jan 2021 | A1 |
| 20210012775 | Kang et al. | Jan 2021 | A1 |
| 20210012776 | Peterson et al. | Jan 2021 | A1 |
| 20210043190 | Wang et al. | Feb 2021 | A1 |
| 20210065698 | Topcu et al. | Mar 2021 | A1 |
| 20210067631 | Van Os et al. | Mar 2021 | A1 |
| 20210072953 | Amarilio et al. | Mar 2021 | A1 |
| 20210074264 | Liang et al. | Mar 2021 | A1 |
| 20210074295 | Moreno et al. | Mar 2021 | A1 |
| 20210082400 | Vishnoi et al. | Mar 2021 | A1 |
| 20210090314 | Hussen et al. | Mar 2021 | A1 |
| 20210092128 | Leblang | Mar 2021 | A1 |
| 20210097998 | Kim et al. | Apr 2021 | A1 |
| 20210104232 | Lee et al. | Apr 2021 | A1 |
| 20210105528 | Van Os et al. | Apr 2021 | A1 |
| 20210110106 | Vescovi et al. | Apr 2021 | A1 |
| 20210110115 | Moritz et al. | Apr 2021 | A1 |
| 20210110254 | Duy et al. | Apr 2021 | A1 |
| 20210124597 | Ramakrishnan et al. | Apr 2021 | A1 |
| 20210127220 | Mathieu et al. | Apr 2021 | A1 |
| 20210134318 | Harvey et al. | May 2021 | A1 |
| 20210141839 | Tang et al. | May 2021 | A1 |
| 20210143987 | Xu et al. | May 2021 | A1 |
| 20210149629 | Martel et al. | May 2021 | A1 |
| 20210149996 | Bellegarda | May 2021 | A1 |
| 20210150151 | Jiaming et al. | May 2021 | A1 |
| 20210151041 | Gruber et al. | May 2021 | A1 |
| 20210151070 | Binder et al. | May 2021 | A1 |
| 20210152684 | Weinstein et al. | May 2021 | A1 |
| 20210165826 | Graham et al. | Jun 2021 | A1 |
| 20210176521 | Matthews | Jun 2021 | A1 |
| 20210182716 | Muramoto et al. | Jun 2021 | A1 |
| 20210191603 | Napolitano et al. | Jun 2021 | A1 |
| 20210191968 | Orr et al. | Jun 2021 | A1 |
| 20210208752 | Hwang | Jul 2021 | A1 |
| 20210208841 | Wilberding | Jul 2021 | A1 |
| 20210216134 | Fukunaga et al. | Jul 2021 | A1 |
| 20210216760 | Dominic et al. | Jul 2021 | A1 |
| 20210224032 | Ryan et al. | Jul 2021 | A1 |
| 20210224474 | Jerome et al. | Jul 2021 | A1 |
| 20210233532 | Aram et al. | Jul 2021 | A1 |
| 20210248804 | Hussen Abdelaziz et al. | Aug 2021 | A1 |
| 20210249009 | Manjunath et al. | Aug 2021 | A1 |
| 20210258881 | Freeman et al. | Aug 2021 | A1 |
| 20210264913 | Schramm et al. | Aug 2021 | A1 |
| 20210264916 | Kim et al. | Aug 2021 | A1 |
| 20210271333 | Hindi et al. | Sep 2021 | A1 |
| 20210273894 | Tian et al. | Sep 2021 | A1 |
| 20210278956 | Dolbakian et al. | Sep 2021 | A1 |
| 20210281965 | Malik et al. | Sep 2021 | A1 |
| 20210294569 | Piersol et al. | Sep 2021 | A1 |
| 20210294571 | Carson et al. | Sep 2021 | A1 |
| 20210295602 | Scapel et al. | Sep 2021 | A1 |
| 20210303116 | Barlow | Sep 2021 | A1 |
| 20210303342 | Dunn et al. | Sep 2021 | A1 |
| 20210304075 | Duong et al. | Sep 2021 | A1 |
| 20210306812 | Gross et al. | Sep 2021 | A1 |
| 20210312930 | Sugaya | Oct 2021 | A1 |
| 20210312931 | Paulik et al. | Oct 2021 | A1 |
| 20210314440 | Matias et al. | Oct 2021 | A1 |
| 20210318901 | Gruber et al. | Oct 2021 | A1 |
| 20210327409 | Naik | Oct 2021 | A1 |
| 20210327410 | Beaufays et al. | Oct 2021 | A1 |
| 20210334528 | Bray et al. | Oct 2021 | A1 |
| 20210335342 | Yuan et al. | Oct 2021 | A1 |
| 20210349605 | Nonaka et al. | Nov 2021 | A1 |
| 20210349608 | Blatz et al. | Nov 2021 | A1 |
| 20210350799 | Hansen et al. | Nov 2021 | A1 |
| 20210350803 | Hansen et al. | Nov 2021 | A1 |
| 20210350810 | Phipps et al. | Nov 2021 | A1 |
| 20210352115 | Hansen et al. | Nov 2021 | A1 |
| 20210357172 | Sinesio et al. | Nov 2021 | A1 |
| 20210365161 | Ellis et al. | Nov 2021 | A1 |
| 20210365174 | Ellis et al. | Nov 2021 | A1 |
| 20210365641 | Zhang et al. | Nov 2021 | A1 |
| 20210366473 | Maeng | Nov 2021 | A1 |
| 20210366480 | Lemay et al. | Nov 2021 | A1 |
| 20210373851 | Stasior et al. | Dec 2021 | A1 |
| 20210375290 | Hu et al. | Dec 2021 | A1 |
| 20210377381 | Aggarwal et al. | Dec 2021 | A1 |
| 20210390259 | Hildick-Smith et al. | Dec 2021 | A1 |
| 20210390955 | Piernot et al. | Dec 2021 | A1 |
| 20210393168 | Santarelli et al. | Dec 2021 | A1 |
| 20210402306 | Huang | Dec 2021 | A1 |
| 20210407318 | Pitschel et al. | Dec 2021 | A1 |
| 20210407502 | Vescovi et al. | Dec 2021 | A1 |
| 20220004825 | Xie et al. | Jan 2022 | A1 |
| 20220013106 | Deng et al. | Jan 2022 | A1 |
| 20220019292 | Lemay et al. | Jan 2022 | A1 |
| 20220021631 | Jina et al. | Jan 2022 | A1 |
| 20220021978 | Gui et al. | Jan 2022 | A1 |
| 20220028387 | Walker et al. | Jan 2022 | A1 |
| 20220030345 | Gong et al. | Jan 2022 | A1 |
| 20220035999 | Pawelec | Feb 2022 | A1 |
| 20220043986 | Nell et al. | Feb 2022 | A1 |
| 20220067283 | Bellegarda et al. | Mar 2022 | A1 |
| 20220068278 | York et al. | Mar 2022 | A1 |
| 20220083986 | Duffy et al. | Mar 2022 | A1 |
| 20220084511 | Nickson et al. | Mar 2022 | A1 |
| 20220093088 | Sridhar et al. | Mar 2022 | A1 |
| 20220093095 | Dighe et al. | Mar 2022 | A1 |
| 20220093101 | Krishnan et al. | Mar 2022 | A1 |
| 20220093109 | Orr et al. | Mar 2022 | A1 |
| 20220093110 | Kim et al. | Mar 2022 | A1 |
| 20220094765 | Niewczas | Mar 2022 | A1 |
| 20220107780 | Gruber et al. | Apr 2022 | A1 |
| 20220122615 | Chen et al. | Apr 2022 | A1 |
| 20220130126 | Delgado et al. | Apr 2022 | A1 |
| 20220139396 | Gada et al. | May 2022 | A1 |
| 20220148587 | Drummie et al. | May 2022 | A1 |
| 20220156041 | Newendorp et al. | May 2022 | A1 |
| 20220157310 | Newendorp et al. | May 2022 | A1 |
| 20220157315 | Raux et al. | May 2022 | A1 |
| 20220197491 | Meyer et al. | Jun 2022 | A1 |
| 20220206298 | Goodman | Jun 2022 | A1 |
| 20220214775 | Shah et al. | Jul 2022 | A1 |
| 20220229985 | Bellegarda et al. | Jul 2022 | A1 |
| 20220230653 | Binder et al. | Jul 2022 | A1 |
| 20220253969 | Kamenetskaya et al. | Aug 2022 | A1 |
| 20220254338 | Gruber et al. | Aug 2022 | A1 |
| 20220254339 | Acero et al. | Aug 2022 | A1 |
| 20220254347 | Lindahl | Aug 2022 | A1 |
| 20220262354 | Greborio et al. | Aug 2022 | A1 |
| 20220264262 | Gruber et al. | Aug 2022 | A1 |
| 20220284901 | Novitchenko et al. | Sep 2022 | A1 |
| 20220293124 | Weinberg et al. | Sep 2022 | A1 |
| 20220293125 | Maddika et al. | Sep 2022 | A1 |
| 20220300094 | Hindi et al. | Sep 2022 | A1 |
| 20220301566 | Van Os et al. | Sep 2022 | A1 |
| 20220329691 | Chinthakunta et al. | Oct 2022 | A1 |
| 20220343066 | Kwong et al. | Oct 2022 | A1 |
| Number | Date | Country |
|---|---|---|
| 2014100581 | Sep 2014 | AU |
| 2015203483 | Jul 2015 | AU |
| 2015101171 | Oct 2015 | AU |
| 2017203668 | Jan 2018 | AU |
| 2018100187 | Mar 2018 | AU |
| 2017222436 | Oct 2018 | AU |
| 2666438 | Jun 2013 | CA |
| 709795 | Dec 2015 | CH |
| 102324233 | Jan 2012 | CN |
| 102340590 | Feb 2012 | CN |
| 102346557 | Feb 2012 | CN |
| 102346719 | Feb 2012 | CN |
| 102368256 | Mar 2012 | CN |
| 102402985 | Apr 2012 | CN |
| 102405463 | Apr 2012 | CN |
| 102449438 | May 2012 | CN |
| 102483915 | May 2012 | CN |
| 102495406 | Jun 2012 | CN |
| 102498457 | Jun 2012 | CN |
| 102510426 | Jun 2012 | CN |
| 102520789 | Jun 2012 | CN |
| 101661754 | Jul 2012 | CN |
| 102629246 | Aug 2012 | CN |
| 102647628 | Aug 2012 | CN |
| 102651217 | Aug 2012 | CN |
| 102663016 | Sep 2012 | CN |
| 102681761 | Sep 2012 | CN |
| 102681896 | Sep 2012 | CN |
| 102682769 | Sep 2012 | CN |
| 102682771 | Sep 2012 | CN |
| 102685295 | Sep 2012 | CN |
| 102693725 | Sep 2012 | CN |
| 102694909 | Sep 2012 | CN |
| 202453859 | Sep 2012 | CN |
| 102708867 | Oct 2012 | CN |
| 102710976 | Oct 2012 | CN |
| 102722478 | Oct 2012 | CN |
| 102737104 | Oct 2012 | CN |
| 102750087 | Oct 2012 | CN |
| 102792320 | Nov 2012 | CN |
| 102801853 | Nov 2012 | CN |
| 102820033 | Dec 2012 | CN |
| 102844738 | Dec 2012 | CN |
| 102866828 | Jan 2013 | CN |
| 102870065 | Jan 2013 | CN |
| 102882752 | Jan 2013 | CN |
| 102890936 | Jan 2013 | CN |
| 102915731 | Feb 2013 | CN |
| 102917004 | Feb 2013 | CN |
| 102917271 | Feb 2013 | CN |
| 102918493 | Feb 2013 | CN |
| 102955652 | Mar 2013 | CN |
| 103035240 | Apr 2013 | CN |
| 103035251 | Apr 2013 | CN |
| 103038728 | Apr 2013 | CN |
| 103064956 | Apr 2013 | CN |
| 103093334 | May 2013 | CN |
| 103093755 | May 2013 | CN |
| 103109249 | May 2013 | CN |
| 103135916 | Jun 2013 | CN |
| 103187053 | Jul 2013 | CN |
| 103197963 | Jul 2013 | CN |
| 103198831 | Jul 2013 | CN |
| 103209369 | Jul 2013 | CN |
| 103217892 | Jul 2013 | CN |
| 103226949 | Jul 2013 | CN |
| 103236260 | Aug 2013 | CN |
| 103246638 | Aug 2013 | CN |
| 103268315 | Aug 2013 | CN |
| 103280218 | Sep 2013 | CN |
| 103282957 | Sep 2013 | CN |
| 103292437 | Sep 2013 | CN |
| 103324100 | Sep 2013 | CN |
| 103327063 | Sep 2013 | CN |
| 103365279 | Oct 2013 | CN |
| 103366741 | Oct 2013 | CN |
| 203249629 | Oct 2013 | CN |
| 103390016 | Nov 2013 | CN |
| 103412789 | Nov 2013 | CN |
| 103414949 | Nov 2013 | CN |
| 103426428 | Dec 2013 | CN |
| 103455234 | Dec 2013 | CN |
| 103456303 | Dec 2013 | CN |
| 103456304 | Dec 2013 | CN |
| 103456306 | Dec 2013 | CN |
| 103457837 | Dec 2013 | CN |
| 103475551 | Dec 2013 | CN |
| 103477592 | Dec 2013 | CN |
| 103533143 | Jan 2014 | CN |
| 103533154 | Jan 2014 | CN |
| 103543902 | Jan 2014 | CN |
| 103546453 | Jan 2014 | CN |
| 103562863 | Feb 2014 | CN |
| 103582896 | Feb 2014 | CN |
| 103593054 | Feb 2014 | CN |
| 103608859 | Feb 2014 | CN |
| 103620605 | Mar 2014 | CN |
| 103645876 | Mar 2014 | CN |
| 103677261 | Mar 2014 | CN |
| 103686723 | Mar 2014 | CN |
| 103714816 | Apr 2014 | CN |
| 103716454 | Apr 2014 | CN |
| 103727948 | Apr 2014 | CN |
| 103730120 | Apr 2014 | CN |
| 103744761 | Apr 2014 | CN |
| 103760984 | Apr 2014 | CN |
| 103761104 | Apr 2014 | CN |
| 103765385 | Apr 2014 | CN |
| 103778527 | May 2014 | CN |
| 103780758 | May 2014 | CN |
| 103792985 | May 2014 | CN |
| 103794212 | May 2014 | CN |
| 103795850 | May 2014 | CN |
| 103809548 | May 2014 | CN |
| 103841268 | Jun 2014 | CN |
| 103885663 | Jun 2014 | CN |
| 103902373 | Jul 2014 | CN |
| 103930945 | Jul 2014 | CN |
| 103942932 | Jul 2014 | CN |
| 103959751 | Jul 2014 | CN |
| 203721183 | Jul 2014 | CN |
| 103971680 | Aug 2014 | CN |
| 104007832 | Aug 2014 | CN |
| 102693729 | Sep 2014 | CN |
| 104036774 | Sep 2014 | CN |
| 104038621 | Sep 2014 | CN |
| 104050153 | Sep 2014 | CN |
| 104090652 | Oct 2014 | CN |
| 104092829 | Oct 2014 | CN |
| 104113471 | Oct 2014 | CN |
| 104125322 | Oct 2014 | CN |
| 104144377 | Nov 2014 | CN |
| 104145304 | Nov 2014 | CN |
| 104169837 | Nov 2014 | CN |
| 104180815 | Dec 2014 | CN |
| 104185868 | Dec 2014 | CN |
| 104219785 | Dec 2014 | CN |
| 104240701 | Dec 2014 | CN |
| 104243699 | Dec 2014 | CN |
| 104281259 | Jan 2015 | CN |
| 104281390 | Jan 2015 | CN |
| 104284257 | Jan 2015 | CN |
| 104284486 | Jan 2015 | CN |
| 104335207 | Feb 2015 | CN |
| 104335234 | Feb 2015 | CN |
| 104350454 | Feb 2015 | CN |
| 104360990 | Feb 2015 | CN |
| 104374399 | Feb 2015 | CN |
| 104423625 | Mar 2015 | CN |
| 104423780 | Mar 2015 | CN |
| 104427104 | Mar 2015 | CN |
| 104463552 | Mar 2015 | CN |
| 104464733 | Mar 2015 | CN |
| 104487929 | Apr 2015 | CN |
| 104516522 | Apr 2015 | CN |
| 104573472 | Apr 2015 | CN |
| 104575493 | Apr 2015 | CN |
| 104575501 | Apr 2015 | CN |
| 104575504 | Apr 2015 | CN |
| 104584010 | Apr 2015 | CN |
| 104584096 | Apr 2015 | CN |
| 104584601 | Apr 2015 | CN |
| 104604274 | May 2015 | CN |
| 104679472 | Jun 2015 | CN |
| 104685898 | Jun 2015 | CN |
| 104699746 | Jun 2015 | CN |
| 104731441 | Jun 2015 | CN |
| 104769584 | Jul 2015 | CN |
| 104769670 | Jul 2015 | CN |
| 104798012 | Jul 2015 | CN |
| 104821167 | Aug 2015 | CN |
| 104821934 | Aug 2015 | CN |
| 104836909 | Aug 2015 | CN |
| 104854583 | Aug 2015 | CN |
| 104867492 | Aug 2015 | CN |
| 104869342 | Aug 2015 | CN |
| 104951077 | Sep 2015 | CN |
| 104967748 | Oct 2015 | CN |
| 104969289 | Oct 2015 | CN |
| 104978963 | Oct 2015 | CN |
| 105025051 | Nov 2015 | CN |
| 105027197 | Nov 2015 | CN |
| 105093526 | Nov 2015 | CN |
| 105100356 | Nov 2015 | CN |
| 105144136 | Dec 2015 | CN |
| 105164678 | Dec 2015 | CN |
| 105164719 | Dec 2015 | CN |
| 105190607 | Dec 2015 | CN |
| 105247511 | Jan 2016 | CN |
| 105247551 | Jan 2016 | CN |
| 105264524 | Jan 2016 | CN |
| 105278681 | Jan 2016 | CN |
| 105320251 | Feb 2016 | CN |
| 105320726 | Feb 2016 | CN |
| 105338425 | Feb 2016 | CN |
| 105379234 | Mar 2016 | CN |
| 105430186 | Mar 2016 | CN |
| 105471705 | Apr 2016 | CN |
| 105472587 | Apr 2016 | CN |
| 105516441 | Apr 2016 | CN |
| 105554217 | May 2016 | CN |
| 105556592 | May 2016 | CN |
| 105808200 | Jul 2016 | CN |
| 105830048 | Aug 2016 | CN |
| 105869641 | Aug 2016 | CN |
| 105872222 | Aug 2016 | CN |
| 105917311 | Aug 2016 | CN |
| 106030699 | Oct 2016 | CN |
| 106062734 | Oct 2016 | CN |
| 106062790 | Oct 2016 | CN |
| 106415412 | Feb 2017 | CN |
| 106462383 | Feb 2017 | CN |
| 106463114 | Feb 2017 | CN |
| 106465074 | Feb 2017 | CN |
| 106471570 | Mar 2017 | CN |
| 106534469 | Mar 2017 | CN |
| 106558310 | Apr 2017 | CN |
| 106773742 | May 2017 | CN |
| 106776581 | May 2017 | CN |
| 107004412 | Aug 2017 | CN |
| 107450800 | Dec 2017 | CN |
| 107480161 | Dec 2017 | CN |
| 107491285 | Dec 2017 | CN |
| 107491468 | Dec 2017 | CN |
| 107491469 | Dec 2017 | CN |
| 107506037 | Dec 2017 | CN |
| 107545262 | Jan 2018 | CN |
| 107608998 | Jan 2018 | CN |
| 107615378 | Jan 2018 | CN |
| 107623616 | Jan 2018 | CN |
| 107786730 | Mar 2018 | CN |
| 107852436 | Mar 2018 | CN |
| 107871500 | Apr 2018 | CN |
| 107919123 | Apr 2018 | CN |
| 107924313 | Apr 2018 | CN |
| 107978313 | May 2018 | CN |
| 108268187 | Jul 2018 | CN |
| 108647681 | Oct 2018 | CN |
| 109447234 | Mar 2019 | CN |
| 109657629 | Apr 2019 | CN |
| 110135411 | Aug 2019 | CN |
| 110263144 | Sep 2019 | CN |
| 105164719 | Nov 2019 | CN |
| 110531860 | Dec 2019 | CN |
| 110598671 | Dec 2019 | CN |
| 110647274 | Jan 2020 | CN |
| 110825469 | Feb 2020 | CN |
| 110945840 | Mar 2020 | CN |
| 111124224 | May 2020 | CN |
| 107123417 | Jun 2020 | CN |
| 111316203 | Jun 2020 | CN |
| 112204507 | Jan 2021 | CN |
| 202016008226 | May 2017 | DE |
| 2431842 | Mar 2012 | EP |
| 2523109 | Nov 2012 | EP |
| 2523188 | Nov 2012 | EP |
| 2551784 | Jan 2013 | EP |
| 2555536 | Feb 2013 | EP |
| 2575128 | Apr 2013 | EP |
| 2632129 | Aug 2013 | EP |
| 2639792 | Sep 2013 | EP |
| 2669889 | Dec 2013 | EP |
| 2672229 | Dec 2013 | EP |
| 2672231 | Dec 2013 | EP |
| 2675147 | Dec 2013 | EP |
| 2680257 | Jan 2014 | EP |
| 2683147 | Jan 2014 | EP |
| 2683175 | Jan 2014 | EP |
| 2672231 | Apr 2014 | EP |
| 2717259 | Apr 2014 | EP |
| 2725577 | Apr 2014 | EP |
| 2733598 | May 2014 | EP |
| 2733896 | May 2014 | EP |
| 2743846 | Jun 2014 | EP |
| 2760015 | Jul 2014 | EP |
| 2779160 | Sep 2014 | EP |
| 2781883 | Sep 2014 | EP |
| 2787683 | Oct 2014 | EP |
| 2801890 | Nov 2014 | EP |
| 2801972 | Nov 2014 | EP |
| 2801974 | Nov 2014 | EP |
| 2824564 | Jan 2015 | EP |
| 2849177 | Mar 2015 | EP |
| 2879402 | Jun 2015 | EP |
| 2881939 | Jun 2015 | EP |
| 2891049 | Jul 2015 | EP |
| 2915021 | Sep 2015 | EP |
| 2930715 | Oct 2015 | EP |
| 2938022 | Oct 2015 | EP |
| 2940556 | Nov 2015 | EP |
| 2947859 | Nov 2015 | EP |
| 2950307 | Dec 2015 | EP |
| 2957986 | Dec 2015 | EP |
| 2973380 | Jan 2016 | EP |
| 2985984 | Feb 2016 | EP |
| 2988513 | Feb 2016 | EP |
| 2891049 | Mar 2016 | EP |
| 3032532 | Jun 2016 | EP |
| 3035329 | Jun 2016 | EP |
| 3038333 | Jun 2016 | EP |
| 3107101 | Dec 2016 | EP |
| 3115905 | Jan 2017 | EP |
| 3125097 | Feb 2017 | EP |
| 2672231 | May 2017 | EP |
| 3161612 | May 2017 | EP |
| 3200185 | Aug 2017 | EP |
| 3224708 | Oct 2017 | EP |
| 3227771 | Oct 2017 | EP |
| 3246916 | Nov 2017 | EP |
| 3270658 | Jan 2018 | EP |
| 3300074 | Mar 2018 | EP |
| 3336805 | Jun 2018 | EP |
| 2973380 | Aug 2018 | EP |
| 2983065 | Aug 2018 | EP |
| 3382530 | Oct 2018 | EP |
| 3392876 | Oct 2018 | EP |
| 3401773 | Nov 2018 | EP |
| 2973002 | Jun 2019 | EP |
| 3506151 | Jul 2019 | EP |
| 3550483 | Oct 2019 | EP |
| 3567584 | Nov 2019 | EP |
| 3323058 | Feb 2020 | EP |
| 3321928 | Apr 2020 | EP |
| 2011MU03716 | Feb 2012 | IN |
| 2012MU01227 | Jun 2012 | IN |
| 2012-14394 | Jan 2012 | JP |
| 2012-502377 | Jan 2012 | JP |
| 2012-22478 | Feb 2012 | JP |
| 2012-33997 | Feb 2012 | JP |
| 2012-37619 | Feb 2012 | JP |
| 2012-40655 | Mar 2012 | JP |
| 2012-63536 | Mar 2012 | JP |
| 2012-508530 | Apr 2012 | JP |
| 2012-89020 | May 2012 | JP |
| 2012-511774 | May 2012 | JP |
| 2012-116442 | Jun 2012 | JP |
| 2012-142744 | Jul 2012 | JP |
| 2012-147063 | Aug 2012 | JP |
| 2012-150804 | Aug 2012 | JP |
| 2012-164070 | Aug 2012 | JP |
| 2012-165084 | Aug 2012 | JP |
| 2012-518847 | Aug 2012 | JP |
| 2012-211932 | Nov 2012 | JP |
| 2012-220959 | Nov 2012 | JP |
| 2013-37688 | Feb 2013 | JP |
| 2013-46171 | Mar 2013 | JP |
| 2013-511214 | Mar 2013 | JP |
| 2013-65284 | Apr 2013 | JP |
| 2013-73240 | Apr 2013 | JP |
| 2013-513315 | Apr 2013 | JP |
| 2013-80476 | May 2013 | JP |
| 2013-517566 | May 2013 | JP |
| 2013-131087 | Jul 2013 | JP |
| 2013-134430 | Jul 2013 | JP |
| 2013-134729 | Jul 2013 | JP |
| 2013-140520 | Jul 2013 | JP |
| 2013-527947 | Jul 2013 | JP |
| 2013-528012 | Jul 2013 | JP |
| 2013-148419 | Aug 2013 | JP |
| 2013-156349 | Aug 2013 | JP |
| 2013-174987 | Sep 2013 | JP |
| 2013-535059 | Sep 2013 | JP |
| 2013-200265 | Oct 2013 | JP |
| 2013-200423 | Oct 2013 | JP |
| 2013-205999 | Oct 2013 | JP |
| 2013-238935 | Nov 2013 | JP |
| 2013-238936 | Nov 2013 | JP |
| 2013-248292 | Dec 2013 | JP |
| 2013-257694 | Dec 2013 | JP |
| 2013-258600 | Dec 2013 | JP |
| 2014-2586 | Jan 2014 | JP |
| 2014-10688 | Jan 2014 | JP |
| 2014-502445 | Jan 2014 | JP |
| 2014-26629 | Feb 2014 | JP |
| 2014-45449 | Mar 2014 | JP |
| 2014-507903 | Mar 2014 | JP |
| 2014-60600 | Apr 2014 | JP |
| 2014-72586 | Apr 2014 | JP |
| 2014-77969 | May 2014 | JP |
| 2014-89711 | May 2014 | JP |
| 2014-109889 | Jun 2014 | JP |
| 2014-124332 | Jul 2014 | JP |
| 2014-126600 | Jul 2014 | JP |
| 2014-127754 | Jul 2014 | JP |
| 2014-140121 | Jul 2014 | JP |
| 2014-518409 | Jul 2014 | JP |
| 2014-142566 | Aug 2014 | JP |
| 2014-145842 | Aug 2014 | JP |
| 2014-146940 | Aug 2014 | JP |
| 2014-150323 | Aug 2014 | JP |
| 2014-519648 | Aug 2014 | JP |
| 2014-524627 | Sep 2014 | JP |
| 2014-191272 | Oct 2014 | JP |
| 2014-219614 | Nov 2014 | JP |
| 2014-222514 | Nov 2014 | JP |
| 2015-1931 | Jan 2015 | JP |
| 2015-4928 | Jan 2015 | JP |
| 2015-8001 | Jan 2015 | JP |
| 2015-12301 | Jan 2015 | JP |
| 2015-18365 | Jan 2015 | JP |
| 2015-501022 | Jan 2015 | JP |
| 2015-501034 | Jan 2015 | JP |
| 2015-504619 | Feb 2015 | JP |
| 2015-41845 | Mar 2015 | JP |
| 2015-52500 | Mar 2015 | JP |
| 2015-60423 | Mar 2015 | JP |
| 2015-81971 | Apr 2015 | JP |
| 2015-83938 | Apr 2015 | JP |
| 2015-94848 | May 2015 | JP |
| 2015-514254 | May 2015 | JP |
| 2015-519675 | Jul 2015 | JP |
| 2015-520409 | Jul 2015 | JP |
| 2015-524974 | Aug 2015 | JP |
| 2015-526776 | Sep 2015 | JP |
| 2015-527683 | Sep 2015 | JP |
| 2015-528140 | Sep 2015 | JP |
| 2015-528918 | Oct 2015 | JP |
| 2015-531909 | Nov 2015 | JP |
| 2016-504651 | Feb 2016 | JP |
| 2016-35614 | Mar 2016 | JP |
| 2016-508007 | Mar 2016 | JP |
| 2016-71247 | May 2016 | JP |
| 2016-119615 | Jun 2016 | JP |
| 2016-151928 | Aug 2016 | JP |
| 2016-524193 | Aug 2016 | JP |
| 2016-156845 | Sep 2016 | JP |
| 2016-536648 | Nov 2016 | JP |
| 2017-11608 | Jan 2017 | JP |
| 2017-19331 | Jan 2017 | JP |
| 2017-516153 | Jun 2017 | JP |
| 2017-123187 | Jul 2017 | JP |
| 2017-211608 | Nov 2017 | JP |
| 2017-537361 | Dec 2017 | JP |
| 6291147 | Feb 2018 | JP |
| 2018-64297 | Apr 2018 | JP |
| 2018-511095 | Apr 2018 | JP |
| 2018-101242 | Jun 2018 | JP |
| 2018-113035 | Jul 2018 | JP |
| 2018-525950 | Sep 2018 | JP |
| 2018-536889 | Dec 2018 | JP |
| 10-2012-0020164 | Mar 2012 | KR |
| 10-2012-0031722 | Apr 2012 | KR |
| 10-2012-0066523 | Jun 2012 | KR |
| 10-2012-0082371 | Jul 2012 | KR |
| 10-2012-0084472 | Jul 2012 | KR |
| 10-1178310 | Aug 2012 | KR |
| 10-2012-0120316 | Nov 2012 | KR |
| 10-2012-0137424 | Dec 2012 | KR |
| 10-2012-0137435 | Dec 2012 | KR |
| 10-2012-0137440 | Dec 2012 | KR |
| 10-2012-0138826 | Dec 2012 | KR |
| 10-2012-0139827 | Dec 2012 | KR |
| 10-1193668 | Dec 2012 | KR |
| 10-2013-0035983 | Apr 2013 | KR |
| 10-2013-0086750 | Aug 2013 | KR |
| 10-2013- 0090947 | Aug 2013 | KR |
| 10-2013- 0108563 | Oct 2013 | KR |
| 10-1334342 | Nov 2013 | KR |
| 10-2013- 0131252 | Dec 2013 | KR |
| -2013- 100133629 | Dec 2013 | KR |
| 10-2014- 0007282 | Jan 2014 | KR |
| 10-2014- 0024271 | Feb 2014 | KR |
| 10-2014- 0025996 | Mar 2014 | KR |
| 10-2014- 0031283 | Mar 2014 | KR |
| 10-2014- 0033574 | Mar 2014 | KR |
| 10-2014- 0042994 | Apr 2014 | KR |
| 10-2014- 0055204 | May 2014 | KR |
| 10-2014-0059697 | May 2014 | KR |
| 10-2014-0068752 | Jun 2014 | KR |
| 10-2014-0071208 | Jun 2014 | KR |
| 10-2014-0088449 | Jul 2014 | KR |
| 10-2014-0093949 | Jul 2014 | KR |
| 10-2014-0106715 | Sep 2014 | KR |
| 10-2014-0107253 | Sep 2014 | KR |
| 10-2014-0147557 | Dec 2014 | KR |
| 10-2015-0006454 | Jan 2015 | KR |
| 10-2015-0013631 | Feb 2015 | KR |
| 10-1506510 | Mar 2015 | KR |
| 10-2015-0038375 | Apr 2015 | KR |
| 10-2015-0039380 | Apr 2015 | KR |
| 10-2015-0041974 | Apr 2015 | KR |
| 10-2015-0043512 | Apr 2015 | KR |
| 10-1510013 | Apr 2015 | KR |
| 10-2015-0062811 | Jun 2015 | KR |
| 10-2015-0095624 | Aug 2015 | KR |
| 10-1555742 | Sep 2015 | KR |
| 10-2015-0113127 | Oct 2015 | KR |
| 10-2015-0131262 | Nov 2015 | KR |
| 10-2015-0138109 | Dec 2015 | KR |
| 10-2016-0004351 | Jan 2016 | KR |
| 10-2016-0010523 | Jan 2016 | KR |
| 10-2016-0040279 | Apr 2016 | KR |
| 10-2016-0055839 | May 2016 | KR |
| 10-2016-0065503 | Jun 2016 | KR |
| 10-2016-0101079 | Aug 2016 | KR |
| 10-2016-0101198 | Aug 2016 | KR |
| 10-2016-0105847 | Sep 2016 | KR |
| 10-2016-0121585 | Oct 2016 | KR |
| 10-2016-0127165 | Nov 2016 | KR |
| 10-2016-0140694 | Dec 2016 | KR |
| 10-2016-0147854 | Dec 2016 | KR |
| 10-2017-0004482 | Jan 2017 | KR |
| 10-2017-0036805 | Apr 2017 | KR |
| 10-2017-0104006 | Sep 2017 | KR |
| 10-2017-0107058 | Sep 2017 | KR |
| 10-1776673 | Sep 2017 | KR |
| 10-2018-0032632 | Mar 2018 | KR |
| 10-2018-0034637 | Apr 2018 | KR |
| 10-2018-0135877 | Dec 2018 | KR |
| 10-1959328 | Mar 2019 | KR |
| 10-2020-0105519 | Sep 2020 | KR |
| 2012141604 | Apr 2014 | RU |
| 201227715 | Jul 2012 | TW |
| 201245989 | Nov 2012 | TW |
| 201312548 | Mar 2013 | TW |
| 201407184 | Feb 2014 | TW |
| 201610982 | Mar 2016 | TW |
| 201629750 | Aug 2016 | TW |
| 2007009225 | Jan 2007 | WO |
| 2010109358 | Sep 2010 | WO |
| 2011088053 | Jul 2011 | WO |
| 2011133573 | Oct 2011 | WO |
| 2011097309 | Dec 2011 | WO |
| 2011088053 | Jan 2012 | WO |
| 2012008434 | Jan 2012 | WO |
| 2012019020 | Feb 2012 | WO |
| 2012019637 | Feb 2012 | WO |
| 2012033312 | Mar 2012 | WO |
| 2012056463 | May 2012 | WO |
| 2012063260 | May 2012 | WO |
| 2012084965 | Jun 2012 | WO |
| 2012092562 | Jul 2012 | WO |
| 2012112331 | Aug 2012 | WO |
| 2012129231 | Sep 2012 | WO |
| 2012063260 | Oct 2012 | WO |
| 2012135157 | Oct 2012 | WO |
| 2012154317 | Nov 2012 | WO |
| 2012154748 | Nov 2012 | WO |
| 2012155079 | Nov 2012 | WO |
| 2012158407 | Nov 2012 | WO |
| 2012160567 | Nov 2012 | WO |
| 2012167168 | Dec 2012 | WO |
| 2012173902 | Dec 2012 | WO |
| 2013009578 | Jan 2013 | WO |
| 2013022135 | Feb 2013 | WO |
| 2013022223 | Feb 2013 | WO |
| 2013048880 | Apr 2013 | WO |
| 2013049358 | Apr 2013 | WO |
| 2013057153 | Apr 2013 | WO |
| 2013101489 | Jul 2013 | WO |
| 2013118988 | Aug 2013 | WO |
| 2013122310 | Aug 2013 | WO |
| 2013128999 | Sep 2013 | WO |
| 2013133533 | Sep 2013 | WO |
| 2013137660 | Sep 2013 | WO |
| 2013163113 | Oct 2013 | WO |
| 2013163857 | Nov 2013 | WO |
| 2013169842 | Nov 2013 | WO |
| 2013173504 | Nov 2013 | WO |
| 2013173511 | Nov 2013 | WO |
| 2013176847 | Nov 2013 | WO |
| 2013184953 | Dec 2013 | WO |
| 2013184990 | Dec 2013 | WO |
| 2014003138 | Jan 2014 | WO |
| 2014004544 | Jan 2014 | WO |
| 2014018580 | Jan 2014 | WO |
| 2014021967 | Feb 2014 | WO |
| 2014022148 | Feb 2014 | WO |
| 2014028735 | Feb 2014 | WO |
| 2014028797 | Feb 2014 | WO |
| 2014031505 | Feb 2014 | WO |
| 2014032461 | Mar 2014 | WO |
| 2014040022 | Mar 2014 | WO |
| 2014046475 | Mar 2014 | WO |
| 2014047047 | Mar 2014 | WO |
| 2014048855 | Apr 2014 | WO |
| 2014066352 | May 2014 | WO |
| 2014070872 | May 2014 | WO |
| 2014073825 | May 2014 | WO |
| 2014078965 | May 2014 | WO |
| 2014093339 | Jun 2014 | WO |
| 2014093911 | Jun 2014 | WO |
| 2014096506 | Jun 2014 | WO |
| 2014124332 | Aug 2014 | WO |
| 2014137074 | Sep 2014 | WO |
| 2014138604 | Sep 2014 | WO |
| 2014143959 | Sep 2014 | WO |
| 2014144395 | Sep 2014 | WO |
| 2014144579 | Sep 2014 | WO |
| 2014144949 | Sep 2014 | WO |
| 2014149473 | Sep 2014 | WO |
| 2014151153 | Sep 2014 | WO |
| 2014124332 | Oct 2014 | WO |
| 2014159578 | Oct 2014 | WO |
| 2014159581 | Oct 2014 | WO |
| 2014162570 | Oct 2014 | WO |
| 2014169269 | Oct 2014 | WO |
| 2014173189 | Oct 2014 | WO |
| 2013173504 | Dec 2014 | WO |
| 2014197336 | Dec 2014 | WO |
| 2014197339 | Dec 2014 | WO |
| 2014197635 | Dec 2014 | WO |
| 2014197730 | Dec 2014 | WO |
| 2014200728 | Dec 2014 | WO |
| 2014204659 | Dec 2014 | WO |
| 2014210392 | Dec 2014 | WO |
| 2015018440 | Feb 2015 | WO |
| 2015020942 | Feb 2015 | WO |
| 2015029379 | Mar 2015 | WO |
| 2015030796 | Mar 2015 | WO |
| 2015036817 | Mar 2015 | WO |
| 2015041882 | Mar 2015 | WO |
| 2015041892 | Mar 2015 | WO |
| 2015047932 | Apr 2015 | WO |
| 2015053485 | Apr 2015 | WO |
| 2015054141 | Apr 2015 | WO |
| 2015080530 | Jun 2015 | WO |
| 2015084659 | Jun 2015 | WO |
| 2015092943 | Jun 2015 | WO |
| 2015094169 | Jun 2015 | WO |
| 2015094369 | Jun 2015 | WO |
| 2015098306 | Jul 2015 | WO |
| 2015099939 | Jul 2015 | WO |
| 2015112625 | Jul 2015 | WO |
| 2015116151 | Aug 2015 | WO |
| 2015121449 | Aug 2015 | WO |
| 2015127404 | Aug 2015 | WO |
| 2015151133 | Oct 2015 | WO |
| 2015153310 | Oct 2015 | WO |
| 2015157013 | Oct 2015 | WO |
| 2015183368 | Dec 2015 | WO |
| 2015183401 | Dec 2015 | WO |
| 2015183699 | Dec 2015 | WO |
| 2015184186 | Dec 2015 | WO |
| 2015184387 | Dec 2015 | WO |
| 2015200207 | Dec 2015 | WO |
| 2016027933 | Feb 2016 | WO |
| 2016028946 | Feb 2016 | WO |
| 2016033257 | Mar 2016 | WO |
| 2016039992 | Mar 2016 | WO |
| 2016040721 | Mar 2016 | WO |
| 2016048789 | Mar 2016 | WO |
| 2016051519 | Apr 2016 | WO |
| 2016052164 | Apr 2016 | WO |
| 2016054230 | Apr 2016 | WO |
| 2016057268 | Apr 2016 | WO |
| 2016075081 | May 2016 | WO |
| 2016085775 | Jun 2016 | WO |
| 2016085776 | Jun 2016 | WO |
| 2016089029 | Jun 2016 | WO |
| 2016100139 | Jun 2016 | WO |
| 2016111881 | Jul 2016 | WO |
| 2016144840 | Sep 2016 | WO |
| 2016144982 | Sep 2016 | WO |
| 2016144983 | Sep 2016 | WO |
| 2016175354 | Nov 2016 | WO |
| 2016187149 | Nov 2016 | WO |
| 2016190950 | Dec 2016 | WO |
| 2016209444 | Dec 2016 | WO |
| 2016209924 | Dec 2016 | WO |
| 2017044160 | Mar 2017 | WO |
| 2017044257 | Mar 2017 | WO |
| 2017044260 | Mar 2017 | WO |
| 2017044629 | Mar 2017 | WO |
| 2017053311 | Mar 2017 | WO |
| 2017058293 | Apr 2017 | WO |
| 2017059388 | Apr 2017 | WO |
| 2017071420 | May 2017 | WO |
| 2017142116 | Aug 2017 | WO |
| 2017160487 | Sep 2017 | WO |
| 2017200777 | Nov 2017 | WO |
| 2017203484 | Nov 2017 | WO |
| 2017213678 | Dec 2017 | WO |
| 2017213682 | Dec 2017 | WO |
| 2017218194 | Dec 2017 | WO |
| 2018009397 | Jan 2018 | WO |
| 2018044633 | Mar 2018 | WO |
| 2018057269 | Mar 2018 | WO |
| 2018067528 | Apr 2018 | WO |
| 2018081833 | May 2018 | WO |
| 2018176053 | Sep 2018 | WO |
| 2018209152 | Nov 2018 | WO |
| 2018213401 | Nov 2018 | WO |
| 2018213415 | Nov 2018 | WO |
| 2018213481 | Nov 2018 | WO |
| 2018217014 | Nov 2018 | WO |
| 2018231307 | Dec 2018 | WO |
| 2019067930 | Apr 2019 | WO |
| 2019078576 | Apr 2019 | WO |
| 2019079017 | Apr 2019 | WO |
| 2019143397 | Jul 2019 | WO |
| 2019147429 | Aug 2019 | WO |
| 2019190646 | Oct 2019 | WO |
| 2019236217 | Dec 2019 | WO |
| 2020010530 | Jan 2020 | WO |
| 2020022572 | Jan 2020 | WO |
| 2020109074 | Jun 2020 | WO |
| 2021054565 | Mar 2021 | WO |
| 2021252230 | Dec 2021 | WO |
| 2022047214 | Mar 2022 | WO |
| Entry |
|---|
| Applicant-Initiated Interview Summary received for U.S. Appl. No. 17/131,267, dated May 20, 2022, 2 pages. |
| Non-Final Office Action received for U.S. Appl. No. 17/131,267, dated Mar. 14, 2022, 11 pages. |
| Notice of Allowance received for U.S. Appl. No. 17/131,267, dated Jun. 17, 2022, 15 pages. |
| Czech Lucas, “A System for Recognizing Natural Spelling of English Words”, Diploma Thesis, Karlsruhe Institute of Technology, May 7, 2014, 107 pages. |
| Aaaaplay, “Sony Media Remote for iOS and Android”, Online available at: <https://www.youtube.com/watch?v=W8QoeQhlGok>, Feb. 4, 2012, 3 pages. |
| Abdelaziz et al., “Speaker-Independent Speech-Driven Visual Speech Synthesis using Domain-Adapted Acoustic Models”, May 15, 2019, 9 pages. |
| Accessibility on iOS, Apple Inc., online available at: https://developer.apple.com/accessibility/ios/, Retrieved on Jul. 26, 2021, 2 pages. |
| “Alexa, Turn Up the Heat! Smartthings Samsung [online]”, Online available at:—<https://web.archive.org/web/20160329142041/https://blog.smartthings.com/news/smartthingsupdates/alexa-turn-up-the-heat/>, Mar. 3, 2016, 3 pages. |
| Alfred App, “Alfred”, Online available at:—<http://www.alfredapp.com/>, retrieved on Feb. 8, 2012, 5 pages. |
| Alsharif et al., “Long Short-Term Memory Neural Network for Keyboard Gesture 6 Decoding”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia, Sep. 2015, 5 pages. |
| Anania Peter, “Amazon Echo with Home Automation (Smartthings)”, Online available at:—<https://www.youtube.com/watch?v=LMW6aXmsWNE>, Dec. 20, 2015, 1 page. |
| Android Authority, “How to use Tasker: A Beginner's Guide”, Online available at:—<https://youtube.com/watch?v= rDpdS_YWzFc>, May 1, 2013, 1 page. |
| Apple Differential Privacy Team, “Learning with Privacy at Scale”, Apple Machine Learning Blog, vol. 1, No. 8, Online available at: <https://machinelearning.apple.com/2017/12/06/learning-with-privacy-at-scale.html>, Dec. 2017, 9 pages. |
| Apple, “Apple previews innovative accessibility features combining the power of hardware, software, and machine learning”, Avialable online at: https://www.apple.com/newsroom/2022/05/apple-previews-innovative-accessibility-features/, May 17, 2022, 10 pages. |
| Apple, “VoiceOver for OS X”, Online available at:—<http://www.apple.com/accessibility/voiceover/>, May 19, 2014, pp. 1-3. |
| Asakura et al., “What LG thinks; How the TV should be in the Living Room”, HiVi, vol. 31, No. 7, Stereo Sound Publishing, Inc., Jun. 17, 2013, pp. 68-71 (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_tT9IAreQ>, Jul. 1, 2013, 3 pages. |
| “Ask Alexa—Things That Are Smart Wiki”, Online available at:—<http://thingsthataresmart.wili/index.php?title=Ask_Alexa&oldid=4283>, Jun. 8, 2016, pp. 1-31. |
| Automate Your Life, “How to Setup Google Home Routines—A Google Home Routines Walkthrough”, Online Available at: <https://www.youtube.com/watch?v=pXokZHP9kZg>, Aug. 12, 2018, 1 page. |
| Badshah, et al., “Deep Features-based Speech Emotion Recognition for Smart Affective Services”, Multimedia Tools and Applications, Oct. 31, 2017, pp. 5571-5589. |
| Bell, Jason, “Machine Learning Hands-On for Developers and Technical Professionals”, Wiley, 2014, 82 pages. |
| Bellegarda, Jeromer, “Chapter 1: Spoken Language Understanding for Natural Interaction: The Siri Experience”, Natural Interaction with Robots, Knowbots and Smartphones, 2014, pp. 3-14. |
| Bellegarda, Jeromer, “Spoken Language Understanding for Natural Interaction: The Siri Experience”, Slideshow retrieved from: <https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.iwsds2012/files/Bellegarda.pdf>, International Workshop on Spoken Dialog Systems (IWSDS), May 2012, pp. 1-43. |
| beointegration.com, “BeoLink Gateway—Programming Example”, Online Available at: <https:/ /www.youtube.com/watch?v=TXDaJFm5UH4>, Mar. 4, 2015, 3 pages. |
| Bodapati et al., “Neural Word Decomposition Models for Abusive Language Detection”, Proceedings of the Third Workshop on Abusive Language Online, Aug. 1, 2019, pp. 135-145. |
| Burgess, Brian, “Amazon Echo Tip: Enable the Wake-Up Sound”, Online available at:—<https://www.groovypost.com/howto/amazon-echo-tip-enable-wake-up-sound/>, Jun. 30, 2015, 4 pages. |
| Butcher, Mike, “EVI Arrives in Town to go Toe-to-Toe with Siri”, TechCrunch, Jan. 23, 2012, pp. 1-2. |
| Büttner et al., “The Design Space of Augmented and Virtual Reality Applications for Assistive Environments in Manufacturing: A Visual Approach”, In Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '17), Island of Rhodes, Greece, online available at: https://dl.acm.org/doi/pdf/10.1145/3056540.3076193, Jun. 21-23, 2017, pp. 433-440. |
| 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. |
| Caraballo et al., “Language Identification Based on a Discriminative Text Categorization Technique”, Iberspeech 2012—VII Jornadas En Tecnologia Del Habla and III Iberian Sltech Workshop, Nov. 21, 2012, pp. 1-10. |
| Castleos, “Whole House Voice Control Demonstration”, Online available at:—<https://www.youtube.com/watch?v=9SRCoxrZ_W4>, Jun. 2, 2012, 1 page. |
| Chang et al., “Monaural Multi-Talker Speech Recognition with Attention Mechanism and Gated Convolutional Networks”, Interspeech 2018, Sep. 2-6, 2018, pp. 1586-1590. |
| Chen et al., “A Convolutional Neural Network with Dynamic Correlation Pooling”, 13th International Conference on Computational Intelligence and Security, IEEE, 2017, pp. 496-499. |
| Chen et al., “Progressive Joint Modeling in Unsupervised Single-Channel Overlapped Speech Recognition”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 26, No. 1, Jan. 2018, pp. 184-196. |
| Chen, Angela, “Amazon's Alexa now handles patient health information”, Available online at: <https://www.theverge.com/2019/4/4/18295260/amazon-hipaa-alexa-echo-patient-health-information-privacy-voice-assistant>, Apr. 4, 2019, 2 pages. |
| Chen, Yi, “Multimedia Siri Finds and Plays Whatever You Ask For”, PSFK Report, Feb. 9, 2012, pp. 1-9. |
| Chenghao, Yuan, “MacroDroid”, Online available at: https://www.ifanr.com/weizhizao/612531, Jan. 25, 2016, 7 pages (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}. |
| Cheyer, Adam, “Adam Cheyer—About”, Online available at:—<http://www.adam.cheyer.com/about.html>, retrieved on Sep. 17, 2012, pp. 1-2. |
| Colt, Sam, “Here's One Way Apple's Smartwatch Could Be Better Than Anything Else”, Business Insider, Aug. 21, 2014, pp. 1-4. |
| Conneau et al., “Supervised Learning of Universal Sentence Representations from Natural Language Inference Data”, Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Copenhagen, Denmark, Sep. 7-11, 2017, pp. 670-680. |
| “Context-Sensitive User Interface”, Online available at: https://web.archive.org/web/20190407003349/https://en.wikipedia.org/wiki/Context-sensitive_user_interface, Apr. 7, 2019, 3 pages. |
| Coulouris, et al., “Distributed Systems: Concepts and Design (Fifth Edition)”, Addison-Wesley, May 7, 2011, 391 pages. |
| Creswell et al., “Generative Adversarial Networks”, IEEE Signal Processing Magazine, Jan. 2018, pp. 53-65. |
| Dai, et al., “Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context”, Online available at: arXiv:1901.02860v3, Jun. 2, 2019, 20 pages. |
| Deedeevuu, “Amazon Echo Alarm Feature”, Online available at:—<https://www.youtube.com/watch?v=fdjU8eRLk7c>, Feb. 16, 2015, 1 page. |
| Delcroix et al., “Context Adaptive Deep Neural Networks for Fast Acoustic Model Adaptation”, ICASSP, 2015, p. 4535-4539. |
| Delcroix et al., “Context Adaptive Neural Network for Rapid Adaptation of Deep CNN Based Acoustic Models”, Interspeech 2016, Sep. 8-12, 2016, pp. 1573-1577. |
| Derrick, Amanda, “How to Set Up Google Home for Multiple Users”, Lifewire, online available at:—<https://www.lifewire.com/set-up-google-home-multiple-users-4685691>, Jun. 8, 2020, 9 pages. |
| Dighe et al., “Lattice-Based Improvements for Voice Triggering Using Graph Neural Networks”, in 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jan. 25, 2020, 5 pages. |
| Dihelson, “How Can I Use Voice or Phrases as Triggers to Macrodroid?”, Macrodroid Forums, Online Available at:—<https://www.tapatalk.com/groups/macrodroid/how-can-i-use-voice-or-phrases-as-triggers-to-macr-t4845.html>, May 9, 2018, 5 pages. |
| “Directv™ Voice”, Now Part of the DIRECTTV Mobile App for Phones, Sep. 18, 2013, 5 pages. |
| Dwork et al., “The Algorithmic Foundations of Differential Privacy”, Foundations and Trends in Theoretical Computer Science: vol. 9: No. 3-4, 211-407, 2014, 281 pages. |
| Earthling1984, “Samsung Galaxy Smart Stay Feature Explained”, Online available at:—<https://www.youtube.com/watch?v=RpjBNtSjupl>, May 29, 2013, 1 page. |
| Eder et al., “At the Lower End of Language—Exploring the Vulgar and Obscene Side of German”, Proceedings of the Third Workshop on Abusive Language Online, Florence, Italy, Aug. 1, 2019, pp. 119-128. |
| Edim, et al., “A Multi-Agent Based Virtual Personal Assistant for E-Health Service”, Journal of Information Engineering and Applications, vol. 3, No. 11, 2013, 9 pages. |
| Evi, “Meet Evi: The One Mobile Application that Provides Solutions for your Everyday Problems”, Feb. 2012, 3 pages. |
| Filipowicz, Luke, “How to use the QuickType keyboard in iOS 8”, Online available at:—<https://www.imore.com/comment/568232>, Oct. 11, 2014, pp. 1-17. |
| Findlater et al., “Beyond QWERTY: Augmenting Touch-Screen Keyboards with Multi-Touch Gestures for Non-Alphanumeric Input”, CHI '12, May 5-10, 2012, 4 pages. |
| Fitzpatrick, Aidan, “Introducing Camo 1.5: AR modes”, Available Online at: “https://reincubate.com/blog/camo-ar-modes-release/”, Oct. 28, 2021, 8 pages. |
| Gadget Hacks, “Tasker Too Complicated? Give MacroDroid a Try [How-To]”, Online available at: <https://www.youtube.com/watch?v=8YL9cWCykKc>, May 27, 2016, 1 page. |
| “Galaxy S7: How to Adjust Screen Timeout & Lock Screen Timeout”, Online available at :—<https://www.youtube.com/watch?v=n6e1WKUS2ww>, Jun. 9, 2016, 1 page. |
| Ganin et al., “Unsupervised Domain Adaptation by Backpropagation”, in Proceedings of the 32nd International Conference on Machine Learning, vol. 37, Jul. 2015, 10 pages. |
| Gatys et al., “Image Style Transfer Using Convolutional Neural Networks”, Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016, pp. 2414-2423. |
| Geyer et al., “Differentially Private Federated Learning: A Client Level Perspective”, arXiv:1712.07557v2, Mar. 2018, 7 pages. |
| Ghauth et al., “Text Censoring System for Filtering Malicious Content Using Approximate String Matching and Bayesian Filtering”, Proc. 4th INNS Symposia Series on Computational Intelligence in Information Systems, Bandar Seri Begawan, Brunei, 2015, pp. 149-158. |
| Gomes et al., “Mining Recurring Concepts in a Dynamic Feature Space”, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, No. 1, Jul. 31, 2013, pp. 95-110. |
| Goodfellow et al., “Generative Adversarial Networks”, Proceedings of the Neural Information Processing Systems, Dec. 2014, 9 pages. |
| Google Developers,“Voice search in your app”, Online available at:—<https://www.youtube.com/watch?v=PS1FbB5qWEI>, Nov. 12, 2014, 1 page. |
| Graves, Alex, “Sequence Transduction with Recurrent Neural Networks”, Proceeding of International Conference of Machine Learning (ICML) Representation Learning Workshop, Nov. 14, 2012, 9 pages. |
| Gu et al., “BadNets: Evaluating Backdooring Attacks on Deep Neural Networks”, IEEE Access, vol. 7, Mar. 21, 2019, pp. 47230-47244. |
| Guim, Mark, “How to Set a Person-Based Reminder with Cortana”, Online available at:—<http://www.wpcentral.com/how-to-person-based-reminder-cortana>, Apr. 26, 2014, 15 pages. |
| Guo et al., “StateLens: A Reverse Engineering Solution for Making Existing Dynamic Touchscreens Accessible”, In Proceedings of the 32nd Annual Symposium on User Interface Software and Technology (UIST '19), New Orleans, La, USA, online available at: https://dl.acm.org/doi/pdf/10.1145/3332165.3347873, Oct. 20-23, 2019, pp. 371-385. |
| Guo et al., “Time-Delayed Bottleneck Highway Networks Using a DFT Feature for Keyword Spotting”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018, 5 pages. |
| Guo et al., “VizLens: A Robust and Interactive Screen Reader for Interfaces in the Real World”, In Proceedings of the 29th Annual Symposium on User Interface Software and Technology (UIST '16), Tokyo, Japan, online available at: https://dl.acm.org/doi/pdf/10.1145/2984511.2984518, Oct. 16-19, 2016, pp. 651-664. |
| Gupta et al., “I-vector-based Speaker Adaptation of Deep Neural Networks for French Broadcast Audio Transcription”, ICASSP, 2014, 2014, pp. 6334-6338. |
| Gupta, Naresh, “Inside Bluetooth Low Energy”, Artech House, 2013, 274 pages. |
| Hardawar, Devindra, “Driving App Waze Builds its own Siri for Hands-Free Voice Control”, Online available at:—<http://venturebeat.com/2012/02/09/driving-app-waze-builds-its-own-siri-for-hands-free-voice-control/>, retrieved on Feb. 9, 2012, 4 pages. |
| Hashimoto, Yoshiyuki, “Simple Guide for iPhone Siri, which can be Operated with your Voice”, Shuwa System Co., Ltd., vol. 1, Jul. 5, 2012, pp. 8, 130, 131. |
| Haung et al., “A Study for Improving Device-Directed Speech Detection Toward Frictionless Human-Machine Interaction”, in Proc. Interspeech, 2019, 5 pages. |
| Hawkeye, “Hawkeye—A better user testing platform”, Online Available at: https://www.youtube.com/watch?v=el0TW0g_76o, Oct. 16, 2019, 3 pages. |
| Hawkeye, “Learn where people look in your products”, Online Available at: https://www.usehawkeye.com, 2019, 6 pages. |
| “Headset Button Controller v7.3 APK Full APP Download for Andriod, Blackberry, iPhone”, Online available at:—<http://fullappdownload.com/headset-button-controller-v7-3-apk/>, Jan. 27, 2014, 11 pages. |
| Heller et al., “AudioScope: Smartphones as Directional Microphones in Mobile Audio Augmented Reality Systems”, In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15), Crossings, Seoul, Korea, online available at: https://dl.acm.org/doi/pdf/10.1145/2702123.2702159, Apr. 18-23, 2015, pp. 949-952. |
| Henderson et al., “Efficient Natural Language Response Suggestion for Smart Reply”, Available Online at: https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/1846e8a466c079eae7e90727e27caf5f98f10e0c.pdf, 2017, 15 pages. |
| Hershey et al., “Deep Clustering: Discriminative Embeddings for Segmentation and Separation”, Proc. ICASSP, Mar. 2016, 6 pages. |
| “Hey Google: How to Create a Shopping List with Your Google Assistant”, Online available at:—<https://www.youtube.com/watch?v=w9NCsElax1Y>, May 25, 2018, 1 page. |
| Hinton et al., “Distilling the Knowledge in a Neural Network”, arXiv preprintarXiv:1503.02531, Mar. 2, 2015, 9 pages. |
| Hook et al., “Automatic speech-based emotion recognition using paralinguistics features”, Bulletin of the Polish Academy of Sciences, Technical Sciences, vol. 67, No. 3, 2019, pp. 479-488. |
| “How to adjust the order of control center buttons on iPhone iOS12 version after buying a mobile phone”, Available online at: https://jingyan.baidu.com/article/5bbb5albbe5a9 713eba1791b.html? Jun. 14, 2019, 4 pages (Official Copy only). {See communication under 37 CFR § 1.98(a) (3)}. |
| “How to Enable Google Assistant on Galaxy S7 and Other Android Phones (No Root)”, Online available at:—<https://www.youtube.com/watch?v=HekIQbWyksE>, Mar. 20, 2017, 1 page. |
| “How to Use Ok Google Assistant Even Phone is Locked”, Online available at:—<https://www.youtube.com/watch?v=9B_gP4j_SP8>, Mar. 12, 2018, 1 page. |
| Hutsko et al., “iPhone All-in-One for Dummies”, 3rd Edition, 2013, 98 pages. |
| id3.org, “id3v2.4.0-Frames”, Online available at:—<http://id3.org/id3v2.4.0-frames?action=print>, retrieved on Jan. 22, 2015, pp. 1-41. |
| Idasallinen, “What's the ‘Like’ Meter Based on?”, Online Available at:—<https://community.spotify.com/t5/Content-Questions/What-s-the-like-meter-based-on/td-p/1209974>, Sep. 22, 2015, 6 pages. |
| Ikeda, Masaru, “beGLOBAL Seoul 2015 Startup Battle: Talkey”, YouTube Publisher, Online Available at:—<https://www.youtube.com/watch?v=4Wkp7sAAldg>, May 14, 2015, 1 page. |
| Inews and Tech, “How to Use the QuickType Keyboard in IOS 8”, Online available at:—<http://www.inewsandtech.com/how-to-use-the-quicktype-keyboard-in-ios-8/>, Sep. 17, 2014, 6 pages. |
| “Interactive Voice”, Online available at:—<http://www.helloivee.com/company/>, retrieved on Feb. 10, 2014, 2 pages. |
| Internet Services and Social Net, “How to Search for Similar Websites”, Online available at: - < https://www.youtube.com/watch?v=nLf2uirpt5s>, see from 0:17 to 1:06, Jul. 4, 2013, 1 page. |
| “iPhone 6 Smart Guide Full Version for SoftBank”, Gijutsu-Hyohron Co., Ltd., vol. 1, Dec. 1, 2014, 4 pages (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}. |
| Isik et al., “Single-Channel Multi-Speaker Separation using Deep Clustering”, Interspeech 2016, Sep. 8-12, 2016, pp. 545-549. |
| Jefford, et al., “Professional BizTalk Server 2006”, Wrox, May 7, 2007, 398 pages. |
| Jeon et al., “Voice Trigger Detection from LVCSR Hypothesis Lattices Using Bidirectional Lattice Recurrent Neural Networks”, International Conference on Acoustics, Speech and Signal Processing (Icassp). IEEE, Feb. 29, 2020, 5 pages. |
| Jeong et al., “Development Trend of N-Screen Service”, Journal of BroadcastingEngineering, vol. 17, No. 1, Sep. 2012, 18 pages (6 pages of English Translation and 12 pages of Official Copy). |
| Jonsson et al., “Proximity-based Reminders Using Bluetooth”, 2014 IEEE International Conference on Pervasive Computing and Communications Demonstrations, 2014, pp. 151-153. |
| Jouvet et al., “Evaluating Grapheme-to-phoneme Converters in Automatic Speech Recognition Context”, IEEE, 2012, pp. 4821-4824. |
| Kannan et al., “Smart Reply: Automated Response Suggestion for Email”, Available Online at: https://arxiv.org/pdf/1606.04870.pdf, Jun. 15, 2016, 10 pages. |
| Karn, Ujjwal, “An Intuitive Explanation of Convolutional Neural Networks”, The Data Science Blog, Aug. 11, 2016, 23 pages. |
| Kastrenakes, Jacob, “Siri's creators will unveil their new Al bot on Monday”, The Verge, online available at: - <https://web.archive.org/web/20160505090418/https://www.theverge.com/2016/May 4, 11 593564/viv-labs-unveiling-monday-new-ai-from-siri-creators>, May 4, 2016, 3 pages. |
| Kazmucha Allyson, “How to Send Map Locations Using iMessage”, iMore.com, Online available at:—<http://www.imore.com/how-use-imessage-share-your-location-your-iphone>, Aug. 2, 2012, 6 pages. |
| Kickstarter, “Ivee Sleek: Wi-Fi Voice-Activated Assistant”, Online available at:—<https://www.kickstarter.com/projects/ivee/ivee-sleek-wi-fi-voice-activated-assistant>, retrieved on Feb. 10, 2014, pp. 1-13. |
| King et al., “Robust Speech Recognition via Anchor Word Representations”, Interspeech 2017, Aug. 20-24, 2017, pp. 2471-2475. |
| Kondrat, Tomek, “Automation for Everyone with MacroDroid”, Online available at: https://www.xda-developers.com/automation-for-everyone-with-macrodroid/, Nov. 17, 2013, 6 pages. |
| Kruger et al., “Virtual World Accessibility with the Perspective Viewer”, Proceedings of ICEAPVI, Athens, Greece, Feb. 12-14, 2015, 6 pages. |
| Kumar, Shiu, “Ubiquitous Smart Home System Using Android Application”, International Journal of Computer Networks & Communications (IJCNC) vol. 6, No. 1, Jan. 2014, pp. 33-43. |
| Kumatani et al., “Direct Modeling of Raw Audio with DNNS for Wake WordDetection”, in 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2017, 6 pages. |
| Lee, Sungjin, “Structured Discriminative Model for Dialog State Tracking”, Proceedings of the SIGDIAL 2013 Conference, Aug. 22-24, 2013, pp. 442-451. |
| Li et al., “Deep neural network for short-text sentiment classification”, International Conference on Database Systems for Advanced Applications, Springer, Cham, 2016, 8 pages. |
| Lin, Luyuan, “An Assistive Handwashing System with Emotional Intelligence”, Using Emotional Intelligence in Cognitive Intelligent Assistant Systems, 2014, 101 pages. |
| “Link Your Voice to Your Devices with Voice Match, Google Assistant Help”, Online available at: <https://support.google.com/assistant/answer/9071681?co=GENIE.Platform%3DAndroid&hl=en>, Retrieved on Jul. 1, 2020, 2 pages. |
| Liou et al., “Autoencoder for Words”, Neurocomputing, vol. 139, Sep. 2014, pp. 84-96. |
| Liu et al., “Accurate Endpointing with Expected Pause Duration”, Sep. 6-10, 2015, pp. 2912-2916. |
| Loukides et al., “What Is the Internet of Things?”, O'Reilly Media, Inc., OnlineAvailable at: <https://www.oreilly.com/library/view/what-is-the/9781491975633/>, 2015, 31 pages. |
| Luo et al., “Speaker-Independent Speech Separation with Deep Attractor Network”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 26, No. 4, Apr. 2018, pp. 787-796. |
| Maas et al., “Combining Acoustic Embeddings and Decoding Features for End-of-Utterance Detection in Real-Time Far-Field Speech Recognition Systems”, in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018, 5 pages. |
| Mallidi et al., “Device-Directed Utterance Detection”, Proc. Interspeech, Aug. 7, 2018, 4 pages. |
| Marketing Land,“Amazon Echo: Play music”, Online Available at:—<https://www.youtube.com/watch?v=A7V5NPbsXi4>, Apr. 27, 2015, 3 pages. |
| “Meet Ivee, Your Wi-Fi Voice Activated Assistant”, Availale Online at:—<http://www.helloivee.com/>, retrieved on Feb. 10, 2014, 8 pages. |
| “Method to Provide Remote Voice Navigation Capability on the Device”, ip.com, Jul. 21, 2016, 4 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. |
| Microsoft Soundscape—A map delivered in 3D sound, Microsoft Research, online available at: https://www.microsoft.com/en-us/research/product/soundscape/, Retrieved on Jul. 26, 2021, 5 pages. |
| Mikolov et al., “Linguistic Regularities in Continuous Space Word Representations”, Proceedings of NAACL-HLT, Jun. 9-14, 2013, pp. 746-751. |
| Miller Chance, “Google Keyboard Updated with New Personalized SuggestionsFeature”, Online available at:—<http://9to5google.com/2014/03/19/google-keyboard-updated-with-new-personalized-suggestions-feature/>, Mar. 19, 2014, 4 pages. |
| Mnih et al., “Human-Level Control Through Deep Reinforcement Learning”, Nature, vol. 518, Feb. 26, 2015, pp. 529-533. |
| “Mobile Speech Solutions, Mobile Accessibility”, SVOX AG Product Information Sheet, online available at:—<http://www.svox.com/site/bra840604/con782768/mob965831936.aSQ?osLang=1>, Sep. 27, 2012, 1 page. |
| Modern Techies,“Braina-Artificial Personal Assistant for PC (like Cortana, Siri)!!!! ”, Online available at: <https://www.youtube.com/watch?v=_Coo2P8ilqQ>, Feb. 24, 2017, 3 pages. |
| Morrison Jonathan, “iPhone 5 Siri Demo”, Online Available at:—<https://www.youtube.com/watch?v=_wHWwG5lhWc>, Sep. 21, 2012, 3 pages. |
| Müller et al., “A Taxonomy for Information Linking in Augmented Reality”, AVR 2016, Part I, LNCS 9768, 2016, pp. 368-387. |
| Muller et al., “Control Theoretic Models of Pointing”, ACM Transactions on Computer-Human Interaction, Aug. 2017, 36 pages. |
| My Cool Aids, “What's New”, Online available at:—<http://www.mycoolaids.com/>, 2012, 1 page. |
| Myers, Brad A., “Shortcutter for Palm”, Available at: <http://www.cs.cmu.edu/˜pebbles/v5/shortcutter/palm/index.html>, retrieved on Jun. 18, 2014, 10 pages. |
| Nakamura et al., “Study of Information Clouding Methods to Prevent Spoilers of Sports Match”, Proceedings of the International Working Conference on Advanced Visual Interfaces (AVI' 12), ISBN: 978-1-4503-1287-5, May 2012, pp. 661-664. |
| Nakamura et al., “Study of Methods to Diminish Spoilers of Sports Match: Potential of a Novel Concept “Information Clouding””, vol. 54, No. 4, ISSN: 1882-7764. Online available at: <https://ipsj.ixsq.nii.ac.jp/ej/index.php?active_action=repository_view_main_item_detail&page_id=13&block_id=8&item_id=91589&item_no=1>, Apr. 2013, pp. 1402-1412 (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}. |
| “Natural Language Interface Using Constrained Intermediate Dictionary of Results”, List of Publications Manually reviewed for the Search of U.S. Pat. No. 7,177,798, Mar. 22, 2013, 1 page. |
| Navigli, Roberto, “Word Sense Disambiguation: A Survey”, ACM Computing Surveys, vol. 41, No. 2, Article 10, Feb. 2009, 69 pages. |
| NDTV, “Sony SmartWatch 2 Launched in India for Rs. 14,990”, available at <http://gadgets.ndtv.com/others/news/sony-smartwatch-2-launched-in-india-for-rs-14990-420319>, Sep. 18, 2013, 4 pages. |
| Norouzian et al., “Exploring Attention Mechanism for Acoustic based Classification of Speech Utterances into System-Directed and Non-System-Directed”, International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, Feb. 1, 2019, 5 pages. |
| “Nuance Dragon Naturally Speaking”, Version 13 End-User Workbook, Nuance Communications Inc., Sep. 2014, 125 pages. |
| Osxdaily, “Get a List of Siri Commands Directly from Siri”, Online available at:—<http://osxdaily.com/2013/02/05/list-siri-commands/>, Feb. 5, 2013, 15 pages. |
| Pak, Gamerz, “Braina: Artificially Intelligent Assistant Software for Windows PC in (urdu / hindhi)”, Online available at: <https://www.youtube.com/watch?v=JH_rMjw8lqc>, Jul. 24, 2018, 3 pages. |
| Pathak et al., “Privacy-preserving Speech Processing: Cryptographic and String-matching Frameworks Show Promise”, In: IEEE signal processing magazine, online available at:—<http://www.merl.com/publications/docs/TR2013-063.pdf>, Feb. 13, 2013, 16 pages. |
| Patra et al., “A Kernel-Based Approach for Biomedical Named Entity Recognition”, Scientific World Journal, vol. 2013, 2013, pp. 1-7. |
| Pavlopoulos et al., “ConvAI at SemEval-2019 Task 6: Offensive Language Identification and Categorization with Perspective and BERT”, Proceedings of the 13th International Workshop on Semantic Evaluation (SemEval-2019), Jun. 6-7, 2019, pp. 571-576. |
| PC Mag, “How to Voice Train Your Google Home Smart Speaker”, Online available at: <https://in.pcmag.com/google-home/126520/how-to-voice-train-your-google-home-smart-speaker>, Oct. 25, 2018, 12 pages. |
| Pennington et al., “GloVe: Global Vectors for Word Representation”, Proceedingsof the Conference on Empirical Methods Natural Language Processing (EMNLP), Doha, Qatar, Oct. 25-29, 2014, pp. 1532-1543. |
| Perlow, Jason, “Alexa Loop Mode with Playlist for Sleep Noise”, Online Available at: <https://www.youtube.com/watch?v=nSkSuXziJSg>, Apr. 11, 2016, 3 pages. |
| Philips, Chris, “Thumbprint Radio: A Uniquely Personal Station Inspired by All of Your Thumbs Up”, Pandora News, Online Available at:—<https://blog.pandora.com/author/chris-phillips/>, Dec. 14, 2015, 7 pages. |
| Phoenix Solutions, Inc., “Declaration of Christopher Schmandt Regarding the MIT Galaxy System”, West Interactive Corp., a Delaware Corporation, Document 40, Jul. 2, 2010, 162 pages. |
| Ping, et al., “Deep Voice 3: Scaling Text to Speech with Convolutional equence Learning”, Available online at: https://arxiv.org/abs/1710.07654, Feb. 22, 2018, 16 pages. |
| pocketables.com,“AutoRemote example profile”, Online available at: https://www.youtube.com/watch?v=kC_zhUnNZj8, Jun. 25, 2013, 1 page. |
| “Pose, Cambridge Dictionary Definition of Pose”, Available online at: <https://dictionary.cambridge.org/dictionary/english/pose>, 4 pages. |
| Qian et al., “Single-channel Multi-talker Speech Recognition with Permutation Invariant Training”, Speech Communication, Issue 104, 2018, pp. 1-11. |
| “Quick Type Keyboard on iOS 8 Makes Typing Easier”, Online available at:—<https://www.youtube.com/watch?v=0CldLR4fhVU>, Jun. 3, 2014, 3 pages. |
| “Radio Stations Tailored to You Based on the Music You Listen to on iTunes”, Apple Announces iTunes Radio, Press Release, Jun. 10, 2013, 3 pages. |
| Rasch, Katharina, “Smart Assistants for Smart Homes”, Doctoral Thesis in Electronic and Computer Systems, 2013, 150 pages. |
| Raux, Antoine, “High-Density Dialog Management the Topic Stack”, Adventures in High Density, Online available at: https://medium.com/adventures-in-high-density/high-density-dialog-management-23efcf91db1e, Aug. 1, 2018, 10 pages. |
| Ravi, Sujith, “Google AI Blog: On-device Machine Intelligence”, Available Online at: https://ai.googleblog.com/2017/02/on-device-machine-intelligence.html, Feb. 9, 2017, 4 pages. |
| Rios Mafe, “New Bar Search for Facebook”, YouTube, available at:—<https://www.youtube.com/watch?v=vwgN1WbvCas>, Jul. 19, 2013, 2 pages. |
| Ritchie, Rene, “QuickType keyboard in iOS 8: Explained”, Online Available at:—<https://www.imore.com/quicktype-keyboards-ios-8-explained>, Jun. 21, 2014, pp. 1-19. |
| Robbins, F Mike, “Automatically place an Android Phone on Vibrate at Work”, Available online at: https://mikefrobbins.com/2016/07/21/automatically-place-an- android-phone-on-vibrate-at-work/, Jul. 21, 2016, pp. 1-11. |
| Rodrigues et al., “Exploring Mixed Reality in Specialized Surgical Environments”, In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA '17), Denver, Co, USA, online available at: https://dl.acm.org/doi/pdf/10.1145/3027063.3053273, May 6-11, 2017, pp. 2591-2598. |
| Ross et al., “Epidemiology as a Framework for Large-Scale Mobile Application Accessibility Assessment”, In Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '17), Baltimore, MD, USA, online available at: https://dl.acm.org/doi/pdf/10.1145/3132525.3132547, Oct. 29-Nov. 1, 2017, pp. 2-11. |
| Routines, “SmartThings Support”, Online available at:—<https://web.archive.org/web/20151207165701/https://support.smartthings.com/hc/en-us/articles/205380034-Routines>, 2015, 3 pages. |
| Rowland et al., “Designing Connected Products: UX for the Consumer Internet of Things”, O'Reilly, May 2015, 452 pages. |
| Samsung Support, “Create a Quick Command in Bixby to Launch Custom Settings by at Your Command”, Online Available at:—<https://www.facebook.com/samsungsupport/videos/10154746303151213>, Nov. 13, 2017, 1 page. |
| Santos et al., “Fighting Offensive Language on Social Media with Unsupervised TextStyle Transfer”, Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (vol. 2: Short Papers), May 20, 2018, 6 pages. |
| Schenk et al., “GazeEverywhere: Enabling Gaze-only User Interaction on an Unmodified Desktop PC in Everyday Scenarios”, In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI'17). ACM, New York, NY, 30343044. Online Available at: https://doi.org/10.1145/3025453.3025455, May 6-11, 2017, 11 pages. |
| Seehafer Brent, “Activate Google Assistant on Galaxy S7 with Screen off”, Online available at:—<https://productforms.google.com/form/#!topic/websearch/lp3q1GBHLVI>, Mar. 8, 2017, 4 pages. |
| Selfridge et al., “Interact: Tightly-coupling Multimodal Dialog with an Interactive Virtual Assistant”, International Conference on Multimodal Interaction, ACM, Nov. 9, 2015, pp. 381-382. |
| Senior et al., “Improving DNN Speaker Independence With I-Vector Inputs”, ICASSP, 2014, pp. 225-229. |
| Seroter et al., “SOA Patterns with BizTalk Server 2013 and Microsoft Azure”, Packt Publishing, Jun. 2015, 454 pages. |
| Settle et al., “End-to-End Multi-Speaker Speech Recognition”, Proc. ICASSP, Apr. 2018, 6 pages. |
| Shen et al., “Style Transfer from Non-Parallel Text by Cross-Alignment”, 31st Conference on Neural Information Processing Systems (NIPS 2017), 2017, 12 pages. |
| Sigtia et al., “Efficient Voice Trigger Detection for Low Resource Hardware”, in Proc. Interspeech 2018, Sep. 2-6, 2018, pp. 2092-2096. |
| Sigtia et al., “Multi-Task Learning for Voice Trigger Detection”, in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, Apr. 20, 2020, 5 pages. |
| Simonite, Tom, “Confronting Siri: Microsoft Launches Digital Assistant Cortana”, 2014, 2 pages (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}. |
| Siou, Serge, “How to Control Apple TV 3rd Generation Using Remote app”, Online available at: <https://www.youtube.com/watch?v=PhyKftZ0S9M>, May 12, 2014, 3 pages. |
| “Skilled at Playing my iPhone 5”, Beijing Hope Electronic Press, Jan. 2013, 6 pages (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}. |
| “SmartThings +Amazon Echo”, Smartthings Samsung [online], Online available at:—<https://web.archive.org/web/20160509231428/https://blog.smartthings.com/featured/a lexa-turn-on-my-smartthings/>, Aug. 21, 2015, 3 pages. |
| Smith, Jake, “Amazon Alexa Calling: How to Set it up and Use it on Your Echo”, iGeneration, May 30, 2017, 5 pages. |
| Song, Yang, “Research of Chinese Continuous Digital Speech Input System Based on HTK”, Computer and Digital Engineering, vol. 40, No. 4, Dec. 31, 2012, 5 pages (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}. |
| Speicher et al., “What is Mixed Reality?”, In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). ACM, Article 537, Glasgow, Scotland, UK, online available at: https://dl.acm.org/doi/pdf/10.1145/3290605.3300767, May 4-9, 2019, 15 pages. |
| Sperber et al., “Self-Attentional Models for Lattice Inputs”, in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, Association for Computational Linguistics, Jun. 4, 2019, 13 pages. |
| SRI, “SRI Speech: Products: Software Development Kits: EduSpeak”, Online available at:—<http://web.archive.org/web/20090828084033/http://www.speechatsri.com/products/eduspeak>shtml, retrieved on Jun. 20, 2013, pp. 1-2. |
| Stent, et al., “Geo-Centric Language Models for Local Business Voice Search”, AT&T Labs—Research, 2009, pp. 389-396. |
| Sundaram et al., “Latent Perceptual Mapping with Data-Driven Variable-Length Acoustic Units for Template-Based Speech Recognition”, ICASSP 2012, Mar. 2012, pp. 4125-4128. |
| Sundermeyer et al., “From Feedforward to Recurrent LSTM Neural Networks for Language Modeling.”, IEEE Transactions to Audio, Speech, and Language Processing, vol. 23, No. 3, Mar. 2015, pp. 517-529. |
| Sundermeyer et al., “LSTM Neural Networks for Language Modeling”, INTERSPEECH 2012, Sep. 9-13, 2012, pp. 194-197. |
| Sutskever et al., “Sequence to Sequence Learning with Neural Networks”, Proceedings of the 27th International Conference on Neural Information Processing Systems, 2014, 9 pages. |
| Tamar et al., “Value Iteration Networks”, Advances in Neural Information Processing Systems, vol. 29, 2016, 16 pages. |
| Tan et al., “Knowledge Transfer in Permutation Invariant Training For Single-channel Multi-talker Speech Recognition”, ICASSP 2018, 2018, pp. 5714-5718. |
| Tech Target Contributor, “AI Accelerator”, Available online at: https://searchenterpriseai.techtarget.com/definition/AI-accelerator, Apr. 2018, 3 pages. |
| Tech With Brett, “Everything the Google Nest Hub Can Do”, Available online at: https://www.youtube.com/watch?v=x3vdytgru2E, Nov. 12, 2018, 13 pages. |
| Tech With Brett, “Google Home Multiple Users Setup”, Available online at: https://www.youtube.com/watch?v=BQOAbRUeFRo&t=257s, Jun. 29, 2017, 4 pages. |
| Tkachenko, Sergey, “Chrome will automatically create Tab Groups”, Available online at: https://winaero.com/chrome-will-automatically-create-tab-groups/, Sep. 18, 2020, 5 pages. |
| Tkachenko, Sergey, “Enable Tab Groups Auto Create in Google Chrome”, Available online at: https://winaero.com/enable-tab-groups-auto-create-in-google- chrome/, Nov. 30, 2020, 5 pages. |
| Tofel et al., “SpeakToit: A Personal Assistant for Older iPhones, iPads”, Apple News, Tips and Reviews, Feb. 9, 2012, 7 pages. |
| Tur, et al., “The CALO Meeting Assistant System”, IEEE Transactions on Audio, Speech, and Language Processing, vol. 18, No. 6, Aug. 2010, pp. 1601-1611. |
| “Use Macrodroid skillfully to automatically clock in with Ding Talk”, Online available at: https://blog.csdn.net/qq_26614295/article/details/84304541, Nov. 20, 2018, 11 pages (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}. |
| Vaswani et al., “Attention Is All You Need”, 31st Conference on Neural Information Processing Systems (NIPS 2017), 2017, pp. 1-11. |
| Vazquez et al., “An Assisted Photography Framework to Help Visually Impaired Users Properly Aim a Camera”, ACM Transactions on Computer-Human Interaction, vol. 21, No. 5, Article 25, Online available at: https://dl.acm.org/doi/pdf/10.1145/2651380, Nov. 2014, 29 pages. |
| Velian Speaks Tech, “10 Google Assistant Tips!”, Available online at: https://www.youtube.com/watch?v=3RNWA3NK9fs, Feb. 24, 2020, 3 pages. |
| Villemure et al., “The Dragon Drive Innovation Showcase: Advancing the State-of-the-art in Automotive Assistants”, 2018, 7 pages. |
| Vodafone Deutschland, “Samsung Galaxy S3 Tastatur Spracheingabe”, Online available at—<https://www.youtube.com/watch?v=6kOd6Gr8uFE>, Aug. 22, 2012, 1 page. |
| Walker, Amy, “NHS Gives Amazon Free Use of Health Data Under Alexa Advice Deal”, Available online at: <https://www.theguardian.com/society/2019/dec/08/nhs-gives-amazon-free-use-of-health-data-under-alexa-advice-deal>, 3 pages. |
| Wang et al., “End-to-end Anchored Speech Recognition”, Proc. ICASSP2019, May 12-17, 2019, 5 pages. |
| Wang, et al., “Tacotron: Towards End-to-End Speech Synthesis”, Available online at: https://arxiv.org/abs/1703.10135, Apr. 6, 2017, 10 pages. |
| Wang, et al., “Training Deep Neural Networks with 8-bit Floating Point Numbers”, 32nd Conference on Neural Information Processing Systems (Neurl PS 2018), 2018, 10 pages. |
| Wei et al., “Design and Implement on Smart Home System”, 2013 Fourth International Conference on Intelligent Systems Design and Engineering Applications, Available online at: https://ieeexplore.ieee.org/document/6843433, 2013, pp. 229-231. |
| Weng et al., “Deep Neural Networks for Single-Channel Multi-Talker Speech Recognition”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 23, No. 10, Oct. 2015, pp. 1670-1679. |
| “What's on Spotify?”, Music for everyone, Online Available at:—<https://web.archive.org/web/20160428115328/https://www.spotify.com/us/>, Apr. 28, 2016, 6 pages. |
| Wikipedia, “Home Automation”, Online Available at:—<https://en.wikipedia.org/w/index.php?title=Home_automation&oldid=686569068>, Oct. 19, 2015, 9 pages. |
| Wikipedia, “Siri”, Online Available at:—<https://en.wikipedia.org/w/index.php?title=Siri&oldid=689697795>, Nov. 8, 2015, 13 Pages. |
| Wikipedia, “Speech Recognition”, available at <http://en.wikipedia.org/wiki/Speech_recognition>, retrieved on Sep. 14, 2011, 12 pages. |
| Wikipedia, “Virtual Assistant”, Wikipedia, Online Available at:—<https://en.wikipedia.org/w/index.php?title=Virtual_assistant&oldid=679330666>, Sep. 3, 2015, 4 pages. |
| Win, et al., “Myanmar Text to Speech System based on Tacotron-2”, International Conference on Information and Communication Tehcnology Convergence (ICTC), Oct. 21-23, 2020, pp. 578-583. |
| “Working with the Dragon Bar”, Nuance Communications, Inc, Jun. 27, 2016, 2 pages. |
| Wu et al., “Monophone-Based Background Modeling for Two-Stage On-device WakeWord Detection”, in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr. 2018, 5 pages. |
| X.AI, “How it Works”, Online available at:—<https://web.archive.org/web/20160531201426/https://x.ai/how-it-works/>, May 31, 2016, 6 pages. |
| Xiang et al., “Correcting Phoneme Recognition Errors in Learning WordPronunciation through Speech Interaction”, Speech Communication, vol. 55, No. 1, Jan. 1, 2013, pp. 190-203. |
| Xu et al., “Policy Optimization of Dialogue Management in Spoken Dialogue System for Out-of-Domain Utterances”, 2016 International Conference on Asian Language Processing (IALP), IEEE, Nov. 21, 2016, pp. 10-13. |
| Xu et al., “Show, Attend and Tell: Neural Image Caption Generation with Visual Attention”, Proceedings of the 32nd International Conference on Machine Learning, Lille, France, 2015, 10 pages. |
| Xu, et al., “Speech-Based Interactive Games for Language Learning: Reading, Translation, and Question-Answering”, Computational Linguistics and Chinese Language Processing, vol. 14, No. 2, Jun. 2009, pp. 133-160. |
| Yan et al., “A Scalable Approach to Using DNN-derived Features in GMM-HMM Based Acoustic Modeling for LVCSR”, 14th Annual Conference of the International Speech Communication Association, InterSpeech 2013, Aug. 2013, pp. 104-108. |
| Yang Astor, “Control Android TV via Mobile Phone APP RKRemoteControl”, Online Available at: <https://www.youtube.com/watch?v=zpmUeOX_xro>, Mar. 31, 2015, 4 pages. |
| Yates Michaelc., “How Can I Exit Google Assistant After I'm Finished with it”, Online available at:—<https://productforums.google.com/forum/#!msg/phone-by-google/faECnR2RJwA/gKNtOkQgAQAJ>, Jan. 11, 2016, 2 pages. |
| Ye et al., “iPhone 4S Native Secret”, Jun. 30, 2012, 1 page (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}. |
| Yeh Jui-Feng, “Speech Act Identification Using Semantic Dependency Graphs with Probabilistic Context-free Grammars”, ACM Transactions on Asian and Low-Resource Language Information Processing, vol. 15, No. 1, Dec. 2015, p. 5.1-5.28. |
| Young et al., “POMDP-Based Statistical Spoken Dialog Systems: A Review”, Proceedings of the IEEE, vol. 101, No. 5, 2013, 18 pages. |
| Yousef, Zulfikara., “Braina (A.I) Artificial Intelligence Virtual Personal Assistant”, Online available at:—<https://www.youtube.com/watch?v=2h6xpB8bPSA>, Feb. 7, 2017, 3 pages. |
| Yu et al., “Permutation Invariant Training of Deep Models for Speaker-Independent Multi-talker Speech Separation”, Proc. ICASSP, 2017, 5 pages. |
| Yu et al., “Recognizing Multi-talker Speech with Permutation Invariant Training”, Interspeech 2017, Aug. 20-24, 2017, pp. 2456-2460. |
| Zainab, “Google Input Tools Shows Onscreen Keyboard in Multiple Languages [Chrome]”, Online available at:—<http://www.addictivetips.com/internet-tips/google-input-tools-shows-multiple-language-onscreen-keyboards-chrome/>, Jan. 3, 2012, 3 pages. |
| Zhan et al., “Play with Android Phones”, Feb. 29, 2012, 1 page (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}. |
| Zhang et al., “Interaction Proxies for Runtime Repair and Enhancement of Mobile Application Accessibility”, In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17). ACM, Denver, CO, USA, online available at: https://dl.acm.org/doi.pdf/10.1145/3025453.3025846, May 6-11, 2017, pp. 6024-6037. |
| Zhang et al., “Very Deep Convolutional Networks for End-to-End Speech Recognition”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017, 5 pages. |
| Zhao et al., “Big Data Analysis and Application”, Aviation Industry Press, Dec. 2015, pp. 236-241 (Official Copy Only). {See communication under 37 CFR § 1.98(a) (3)}. |
| Zhao et al., “CueSee: Exploring Visual Cues for People with Low Vision to Facilitate a Visual Search Task”, In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, UbiComp '16, Heidelberg, Germany, online available at: https://dl.acm.org/doi/pdf/10.1145/2971648.2971730, Sep. 12-16, 2016, pp. 73-84. |
| Zhao et al., “Enabling People with Visual Impairments to Navigate Virtual Reality with a Haptic and Auditory Cane Simulation”, In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, Article 116, Montréal, QC, Canada, online available at: https://dl.acm.org/doi/pdf/10.1145/3173574.3173690, Apr. 21-26, 2018, 14 pages. |
| Zhao et al., “SeeingVR: A Set of Tools to Make Virtual Reality More Accessible to People with Low Vision”, In Proceedings of the 2019 CHI Conference on HumanFactors in Computing Systems (CHI '19). ACM, Article 111, Glasgow, Scotland, UK, online available at: https://dl.acm.org/doi/pdf/10.1145/3290605.3300341, May 4-9, 2019, 14 pages. |
| Zhao et al., “Transferring Age and Gender Attributes for Dimensional Emotion Prediction from Big Speech Data Using Hierarchical Deep Learning”, 2018 4th IEEE International Conference on Big Data Security on Cloud, 2018, pp. 20-24. |
| Zheng, et al., “Intent Detection and Semantic Parsing for Navigation Dialogue Language Processing”, 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), 2017, 6 pages. |
| Zhong et al., “JustSpeak: Enabling Universal Voice Control on Android”, W4A'14, Proceedings of the 11th Web for All Conference, No. 36, Apr. 7-9, 2014, 8 pages. |
| Zhou et al., “Learning Dense Correspondence via 3D-guided Cycle Consistency”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, 10 pages. |
| Zmolikova et al., “Speaker-Aware Neural Network Based Beamformer for Speaker Extraction in Speech Mixtures”, Interspeech 2017, Aug. 20-24, 2017, pp. 2655-2659. |
| Number | Date | Country | |
|---|---|---|---|
| 20230048256 A1 | Feb 2023 | US |
| Number | Date | Country | |
|---|---|---|---|
| 63054178 | Jul 2020 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 17131267 | Dec 2020 | US |
| Child | 17973341 | US |
