Multi-state digital assistant for continuous conversation

Abstract

The present disclosure relates to a multi-state digital assistant for continuous conversation. Systems and processes for operating an intelligent automated assistant are provided. For example, a first voice input is received from a user. In response to receiving the first voice input, a response is provided. A first output corresponding to the digital assistant in a first state is provided, and a second voice input is received from the user. A first plurality of values ​​is obtained. Based on the first plurality of values, a first confidence level is obtained corresponding to the second voice input. Based on determining that the first confidence level exceeds a first threshold confidence level, a second output corresponding to the digital assistant in a second state is provided. The second voice input is continued to be received.

Description

Technical Field

[0001] The present invention relates generally to intelligent automated assistants and, more particularly, to facilitating a continuous conversation with a digital assistant. Background Art

[0002] Intelligent automated assistants (or digital assistants) can provide a convenient interface between human users and electronic devices. Such assistants can allow users to interact with devices or systems using natural language in the form of speech and / or text. For example, a user can provide voice input containing a user request to a digital assistant running on an electronic device. The digital assistant can interpret the user's intent from the voice input and operationalize the user's intent into tasks. These tasks can then be performed by executing one or more services of the electronic device, and relevant output responsive to the user's request can be returned to the user.

[0003] During a user's interaction with a digital assistant, user input and digital assistant responses may be exchanged. The interaction may include multiple rounds of exchanges between the user and the assistant. However, conventional digital assistant systems typically do not include capabilities to facilitate robust interactions between the user and the digital assistant. For example, conventional systems typically do not include multiple speech analysis phases applied to subsequent speech from the user, such as a first phase to analyze a first set of values ​​and a second phase to analyze a second set of values. These systems also do not allow the user to dynamically interrupt or correct the digital assistant, if necessary. Therefore, there is a need for an improved digital assistant system with continuous conversation capabilities. Summary of the Invention

[0004] The present invention provides systems and processes for operating an intelligent automated assistant. For example, a first voice input is received from a user. In response to receiving the first voice input, a response is provided. A first output corresponding to the digital assistant in a first state is provided, and a second voice input is received from the user. A first plurality of values ​​is obtained. Based on the first plurality of values, a first confidence level corresponding to the second voice input is obtained. Based on determining that the first confidence level exceeds a first threshold confidence level, a second output corresponding to the digital assistant in a second state is provided. The second voice input is continued to be received. BRIEF DESCRIPTION OF THE DRAWINGS

[0005] Figure 1 A block diagram illustrating systems and environments for implementing a digital assistant according to various examples.

[0006] Figure 2A A block diagram of a portable multifunction device that implements the client-side portion of a digital assistant according to various examples is shown.

[0007] Figure 2B is a block diagram illustrating exemplary components for event processing according to various examples.

[0008] Figure 3 A portable multifunction device implementing the client-side portion of a digital assistant according to various examples is shown.

[0009] Figure 4 is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface according to various examples.

[0010] Figure 5A An exemplary user interface is shown for a menu of applications on a portable multifunction device according to various examples.

[0011] Figure 5B Exemplary user interfaces for a multifunction device with a touch-sensitive surface separate from the display are shown according to various examples.

[0012] Figure 6A A personal electronic device according to various examples is shown.

[0013] Figure 6B is a block diagram illustrating a personal electronic device according to various examples.

[0014] Figure 7A A block diagram of a digital assistant system or a server portion thereof according to various examples is shown.

[0015] Figure 7B Shown in accordance with various examples Figure 7A The capabilities of the digital assistant shown in .

[0016] Figure 7C A portion of an ontology according to various examples is shown.

[0017] Figure 8 A process for facilitating a continuous conversation with a digital assistant according to various examples is shown.

[0018] Figure 9 A process for facilitating a continuous conversation with a digital assistant according to various examples is shown.

[0019] Figure 10 A process for facilitating a continuous conversation with a digital assistant according to various examples is shown.

[0020] Figures 11A to 11B A process for facilitating a continuous conversation with a digital assistant according to various examples is shown. DETAILED DESCRIPTION

[0021] In the following description of the examples, reference is made to the accompanying drawings, which show, by way of illustration, specific examples that may be implemented. It should be understood that other examples may be used and structural changes may be made without departing from the scope of the various examples.

[0022] Conventional techniques for continuous digital assistant interaction generally lack effectiveness. Specifically, exemplary conventional systems do not include a robust framework for handling "follow-up" speech, or speech directed to a previous user request and / or digital assistant response, such as a multi-state framework that considers specific values ​​based on the current context or state. In contrast, conventional systems generally focus on cues related to speech, rather than additional multimodal input related to the user and device (e.g., gaze, attention, device motion, speaker identification, etc.). Consequently, these systems do not provide an efficient and seamless means by which a user can interact with the device.

[0023] Although the following description uses the terms "first," "second," etc. to describe various elements, these elements should not be limited by these terms. These terms are simply used to distinguish one element from another. For example, without departing from the scope of the various described examples, a first input may be referred to as a second input, and similarly, a second input may be referred to as a first input. Both the first input and the second input are inputs, and in some cases, are independent and distinct inputs.

[0024] The terms used in the description of the various described examples herein are for the purpose of describing specific examples only and are not intended to be limiting. As used in the description of the various described examples and in 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" used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will also be 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 parts, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts, and / or groupings thereof.

[0025] Depending on the context, the term "if" may be interpreted to mean "when" or "upon" or "in response to determining" or "in response to detecting." Similarly, depending on the context, the phrase "if it is determined that..." or "if [stated condition or event] is detected" may be interpreted to mean "upon determining that..." or "in response to determining that..." or "upon detecting [stated condition or event]" or "in response to detecting [stated condition or event]."

[0026] 1. System and Environment

[0027] Figure 1A block diagram of a system 100 according to various examples is shown. In some examples, the system 100 implements a digital assistant. The terms "digital assistant," "virtual assistant," "intelligent automated assistant," or "automated digital assistant" refer to any information processing system that interprets natural language input in spoken and / or textual form to infer user intent and performs actions based on the inferred user intent. For example, to act on an inferred user intent, the system performs one or more of the following steps: identifying a task flow having steps and parameters designed to implement the inferred user intent, inputting specific requirements into the task flow based on the inferred user intent; executing the task flow by calling a program, method, service, API, etc.; and generating an output response to the user in an audible (e.g., voice) and / or visual form.

[0028] Specifically, digital assistants are capable of accepting user requests that are at least partially in the form of natural language commands, requests, statements, narrations, and / or inquiries. Typically, user requests seek an informational answer from the digital assistant or the performance of a task. A satisfactory response to a user request includes providing the requested informational answer, performing the requested task, or a combination of the two. For example, a user asks the digital assistant a question such as, "Where am I now?" Based on the user's current location, the digital assistant responds, "You are near the West Gate of Central Park." The user also requests a task, such as, "Please invite my friends to my girlfriend's birthday party next week." In response, the digital assistant may acknowledge the request by saying, "Okay, right away," and then send appropriate calendar invitations on behalf of the user to each of the user's friends listed in the user's electronic address book. While performing the requested task, the digital assistant sometimes interacts with the user in a continuous conversation involving multiple information exchanges over an extended period of time. There are many other ways to interact with a digital assistant to request information or perform various tasks. In addition to providing verbal responses and taking programmed actions, digital assistants also provide responses in other visual or audio forms, such as text, alerts, music, videos, animations, and the like.

[0029] like Figure 1 As shown, in some examples, the digital assistant is implemented according to a client-server model. The digital assistant includes a client-side portion 102 (hereinafter referred to as "DA client 102") executing on a user device 104 and a server-side portion 106 (hereinafter referred to as "DA server 106") executing on a server system 108. The DA client 102 communicates with the DA server 106 via one or more networks 110. The DA client 102 provides client-side functionality, such as input and output processing for the user, and communication with the DA server 106. The DA server 106 provides server-side functionality for any number of DA clients 102, each located on a corresponding user device 104.

[0030] In some examples, the DA server 106 includes a client-facing I / O interface 112, one or more processing modules 114, data and models 116, and an I / O interface to external services 118. The client-facing I / O interface 112 facilitates client-facing input and output processing of the DA server 106. The one or more processing modules 114 utilize the data and models 116 to process voice input and determine user intent based on the natural language input. In addition, the one or more processing modules 114 perform task execution based on the inferred user intent. In some examples, the DA server 106 communicates with external services 120 over one or more networks 110 to complete tasks or collect information. The I / O interface 118 to external services facilitates such communications.

[0031] User device 104 can be any suitable electronic device. In some examples, user device 104 is a portable multifunction device (e.g., Figure 2A The device 200), multifunctional device (for example, Figure 4 The device 400) or a personal electronic device (eg, Figures 6A to 6B The portable multifunction device is, for example, a mobile phone that also includes other functions (such as a PDA and / or music player functions). Specific examples of portable multifunction devices include the Apple iPod and Device. Other examples of portable multifunction devices include, but are not limited to, earbuds / headphones, speakers, and laptops or tablets. In addition, in some examples, user device 104 is a non-portable multifunction device. Specifically, user device 104 is a desktop computer, a game console, a speaker, a television, or a television set-top box. In some examples, user device 104 includes a touch-sensitive surface (e.g., a touch screen display and / or a touchpad). In addition, user device 104 optionally includes one or more other physical user interface devices, such as a physical keyboard, a mouse, and / or a joystick. Various examples of electronic devices such as multifunction devices are described in more detail below.

[0032] Examples of the one or more communication networks 110 include local area networks (LANs) and wide area networks (WANs), such as the Internet. The one or more communication networks 110 are implemented using any known network protocol, including various wired or wireless protocols such as 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.

[0033] The server system 108 is implemented on one or more stand-alone data processing devices or a distributed computer network. In some examples, the server system 108 also uses various virtual devices and / or services of third-party service providers (e.g., third-party cloud service providers) to provide the potential computing resources and / or infrastructure resources of the server system 108.

[0034] In some examples, the user device 104 communicates with the DA server 106 via a second user device 122. The second user device 122 is similar or identical to the user device 104. For example, the second user device 122 is similar to the user device 104 described below with reference to FIG. Figure 2A 、 Figure 4 as well as Figures 6A to 6B The device 200, 400 or 600 described. The user device 104 is configured to be communicatively coupled to the second user device 122 via a direct communication connection (such as, Bluetooth, NFC, BTLE, etc.) or via a wired or wireless network (such as, a local Wi-Fi network). In some examples, the second user device 122 is configured to act as a proxy between the user device 104 and the DA server 106. For example, the DA client 102 of the user device 104 is configured to transmit information (e.g., a user request received at the user device 104) to the DA server 106 via the second user device 122. The DA server 106 processes the information and returns relevant data (e.g., data content in response to the user request) to the user device 104 via the second user device 122.

[0035] In some examples, the user device 104 is configured to send an abbreviated request for data to a second user device 122 to reduce the amount of information transmitted from the user device 104. The second user device 122 is configured to determine supplemental information to add to the abbreviated request to generate a complete request for transmission to the DA server 106. The system architecture can advantageously allow user devices 104 with limited communication capabilities and / or limited battery power (e.g., a watch or similar compact electronic device) to access services provided by the DA server 106 by using a second user device 122 with greater communication capabilities and / or battery power (e.g., a mobile phone, laptop, tablet, etc.) as a proxy to the DA server 106. Although Figure 1 Only two user devices 104 and 122 are shown, but it should be understood that in some examples, the system 100 may include any number and type of user devices configured to communicate with the DA server system 106 in this proxy configuration.

[0036] Although Figure 1 The digital assistant shown in includes both a client-side portion (e.g., DA client 102) and a server-side portion (e.g., DA server 106), but in some examples, the functionality of the digital assistant is implemented as a stand-alone application installed on a user device. Furthermore, the division of functionality between the client and server portions of the digital assistant can vary in different implementations. For example, in some examples, the DA client is a thin client that provides only user-facing input and output processing functionality and delegates all other functionality of the digital assistant to a backend server.

[0037] 2. Electronic devices

[0038] Attention now turns to embodiments of electronic devices for implementing the client-side portion of the digital assistant. Figure 2A2 is a block diagram illustrating a portable multifunction device 200 with a touch-sensitive display system 212 according to some embodiments. The touch-sensitive display 212 is sometimes referred to as a "touch screen" for convenience, and is sometimes referred to as or referred to as a "touch-sensitive display system." The device 200 includes memory 202 (which optionally includes one or more computer-readable storage media), a memory controller 222, one or more processing units (CPUs) 220, a peripheral device interface 218, RF circuitry 208, audio circuitry 210, a speaker 211, a microphone 213, an input / output (I / O) subsystem 206, other input control devices 216, and external ports 224. The device 200 optionally includes one or more optical sensors 264. The device 200 optionally includes one or more contact intensity sensors 265 for detecting the intensity of contacts on the device 200 (e.g., a touch-sensitive surface of the device 200 such as the touch-sensitive display system 212). Device 200 optionally includes one or more tactile output generators 267 for generating tactile output on device 200 (e.g., generating tactile output on a touch-sensitive surface such as touch-sensitive display system 212 of device 200 or trackpad 455 of device 400). These components optionally communicate via one or more communication buses or signal lines 203.

[0039] As used in this 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 surrogate (surrogate) 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 different values ​​and more typically includes hundreds of different values ​​(e.g., at least 256). The intensity of a contact is optionally determined (or measured) using various methods and various sensors or combinations of sensors. For example, one or more force sensors below or adjacent to the touch-sensitive surface are optionally used to measure the force at different points on the touch-sensitive surface. In some implementations, force measurements from multiple force sensors are combined (e.g., weighted averaged) to determine an estimated contact force. Similarly, the pressure-sensitive tip of a stylus is optionally used to determine the pressure of the stylus on the touch-sensitive surface. Alternatively, the size of the contact area detected on the touch-sensitive surface and / or its change, the capacitance of the touch-sensitive surface near the contact and / or its change, and / or the resistance of the touch-sensitive surface near the contact and / or its change are optionally used as a surrogate for the force or pressure of the contact on the touch-sensitive surface. In some embodiments, the surrogate measurement of the contact force or pressure is used directly to determine whether an intensity threshold has been exceeded (e.g., the intensity threshold is described in units corresponding to the surrogate measurement). In some embodiments, the surrogate measurement of the contact force or pressure is converted into 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 the contact as an attribute of the user input allows the user to access additional device functionality that would otherwise be inaccessible to the user on a smaller device with limited real estate, which is used to display an indication (e.g., on a touch-sensitive display) and / or receive user input (e.g., via a touch-sensitive display, touch-sensitive surface, or physical / mechanical controls, such as knobs or buttons).

[0040] As used in this specification and claims, the term "tactile output" refers to a physical displacement of a device relative to a previous position of the device, a physical displacement of a component of a device (e.g., a touch-sensitive surface) relative to another component of the device (e.g., a housing), or a displacement of a component relative to the center of mass of the device that will be detected by a user using the user's sense of touch. For example, when a device or a component of the device is in contact with a surface that is touch-sensitive to a user (e.g., a finger, palm, or other part of the user's hand), the tactile output generated by the physical displacement will be interpreted by the user as a tactile sensation that corresponds to a perceived change in a physical characteristic of the device or 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 "press click" or "release click" on a physical actuation button. In some cases, the user will feel a tactile sensation, such as a "press click" or "release click," even when the physical actuation button associated with the touch-sensitive surface that was physically pressed (e.g., displaced) by the user's movement does not move. As another example, even when the smoothness of the touch-sensitive surface does not change, movement of the touch-sensitive surface may optionally be interpreted or sensed by the user as "roughness" of the touch-sensitive surface. While such a user's interpretation of touch will be limited by the user's individualized sensory perceptions, many sensory perceptions of touch are common to most users. Thus, when a tactile output is described as corresponding to a particular sensory perception of a user (e.g., "press click," "release click," "roughness"), unless otherwise stated, the generated tactile output corresponds to a physical displacement of the device or a component thereof that would generate that sensory perception for a typical (or average) user.

[0041] It should be understood 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. Figure 2A The various components shown in the EMBODIMENTS 100 are implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and / or application specific integrated circuits.

[0042] Memory 202 includes one or more computer-readable storage media. These computer-readable storage media 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.

[0043] In some examples, the non-transitory computer-readable storage medium of memory 202 is used to store instructions (e.g., for performing various aspects of the processes described below) for use by or in conjunction with an instruction execution system, apparatus, or device, such as a computer-based system, a system containing a processor, or other system that can retrieve instructions from an instruction execution system, apparatus, or device and execute the instructions. In other examples, the instructions (e.g., for performing various aspects of the processes described below) are stored on a non-transitory computer-readable storage medium (not shown) of server system 108 or divided between the non-transitory computer-readable storage medium of memory 202 and the non-transitory computer-readable storage medium of server system 108.

[0044] The peripheral device interface 218 is used to couple the input and output peripheral devices of the device to the CPU 220 and the memory 202. The one or more processors 220 run or execute various software programs and / or instruction sets stored in the memory 202 to perform various functions of the device 200 and process data. In some embodiments, the peripheral device interface 218, the CPU 220, and the memory controller 222 are implemented on a single chip, such as the chip 204. In some other embodiments, they are implemented on separate chips.

[0045] RF (radio frequency) circuitry 208 receives and transmits RF signals, also known as electromagnetic signals. RF circuitry 208 converts electrical signals into / from electromagnetic signals and communicates with communication networks and other communication 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 the like. RF circuitry 208 optionally communicates with networks and other devices via wireless communications, such as the Internet (also known as the World Wide Web (WWW)), intranets, and / or wireless networks (such as cellular telephone networks, wireless local area networks (LANs), and / or metropolitan area networks (MANs)). RF circuitry 208 optionally includes well-known circuitry for detecting near-field communication (NFC) fields, such as via a short-range communication radio. Wireless communication optionally uses any of a variety of communication 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 802.11b), IEEE 802.11c, IEEE 802.11d ... 11n and / or IEEE 802.11ac), Voice over Internet Protocol (VoIP), Wi-MAX, email protocols (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 that have not yet been developed as of the filing date of this document.

[0046] The audio circuit 210, speaker 211, and microphone 213 provide an audio interface between the user and the device 200. The audio circuit 210 receives audio data from the peripheral device interface 218, converts the audio data into electrical signals, and transmits the electrical signals to the speaker 211. The speaker 211 converts the electrical signals into sound waves audible to humans. The audio circuit 210 also receives electrical signals converted from sound waves by the microphone 213. The audio circuit 210 converts the electrical signals into audio data and transmits the audio data to the peripheral device interface 218 for processing. The audio data is retrieved from and / or transmitted to the memory 202 and / or the RF circuit 208 via the peripheral device interface 218. In some embodiments, the audio circuit 210 also includes a headset jack (e.g., Figure 3 The headset jack provides an interface between the audio circuitry 210 and a removable audio input / output peripheral device, such as an output-only headset or a headset with both output (e.g., a single or dual-ear headset) and input (e.g., a microphone).

[0047] The I / O subsystem 206 couples input / output peripherals on the device 200, such as the touch screen 212 and other input control devices 216, to the peripheral device interface 218. The I / O subsystem 206 optionally includes a display controller 256, an optical sensor controller 258, an intensity sensor controller 259, a tactile 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, slide switches, joysticks, click wheels, etc. In some alternative embodiments, the input controller 260 is optionally coupled to any (or none) of the following: a keyboard, an infrared port, a USB port, and a pointing device such as a mouse. One or more buttons (e.g., Figure 3 308) optionally includes an up / down button for volume control of the speaker 211 and / or microphone 213. The one or more buttons optionally include a push button (e.g., Figure 3 306 in ).

[0048] A quick press of the push button releases the lock on the touch screen 212 or initiates the process of unlocking the device using gestures on the touch screen, as described in U.S. Patent Application No. 11 / 322,549, filed on December 23, 2005, entitled "Unlocking a Device by Performing Gestures on an Unlock Image," which is hereby incorporated by reference in its entirety. A longer press of the push button (e.g., 306) turns the device 200 on or off. The user can customize the function of one or more buttons. The touch screen 212 is used to implement virtual buttons or soft buttons and one or more soft keyboards.

[0049] The touch-sensitive display 212 provides an input interface and an output interface between the device and the user. The display controller 256 receives electrical signals from the touch screen 212 and / or sends electrical signals to the touch screen 212. The touch screen 212 displays visual output to the user. The visual output includes graphics, text, icons, videos, and any combination thereof (collectively referred to as "graphics"). In some embodiments, some or all of the visual output corresponds to user interface objects.

[0050] The touch screen 212 has a touch-sensitive surface, sensor, or sensor group that accepts input from the user based on tactile and / or haptic contact. The touch screen 212 and display controller 256 (together with any associated modules and / or instruction sets in memory 202) detect contact on the touch screen 212 (and any movement or interruption of that contact) and convert the detected contact into interaction with a user interface object (e.g., one or more soft keys, icons, web pages, or images) displayed on the touch screen 212. In an exemplary embodiment, the point of contact between the touch screen 212 and the user corresponds to the user's finger.

[0051] The 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. The touch screen 212 and display controller 256 use any of a variety 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 the touch screen 212 to detect contact and any movement or interruption thereof. In an exemplary embodiment, projected mutual capacitance sensing technology is used, such as in the Apple ® Touch Controller from Apple Inc. (Cupertino, California). and iPod The technology used in

[0052] In some embodiments, the touch-sensitive display of the touch screen 212 is similar to the multi-touch-sensitive trackpads described in U.S. Patents 6,323,846 (Westerman et al.), 6,570,557 (Westerman et al.), and / or 6,677,932 (Westerman), and / or U.S. Patent Publication 2002 / 0015024A1, each of which is hereby incorporated by reference in its entirety. However, the touch screen 212 displays visual output from the device 200, whereas a touch-sensitive trackpad does not provide visual output.

[0053] In some embodiments, the touch-sensitive display of the touch screen 212 is as described in the following applications: (1) U.S. patent application No. 11 / 381,313, filed on May 2, 2006, entitled "Multipoint Touch Surface Controller"; (2) U.S. patent application No. 10 / 840,862, filed on May 6, 2004, entitled "Multipoint Touchscreen"; (3) U.S. patent application No. 10 / 903,964, filed on July 30, 2004, entitled "Gestures For Touch Sensitive Input Devices"; (4) U.S. patent application No. 11 / 048,264, filed on January 31, 2005, entitled "Gestures For Touch Sensitive Input Devices"; (5) U.S. patent application No. 11 / 050,694, filed on January 18, 2005, entitled "Mode-Based Graphical User Interfaces For Touch Sensitive Input Devices”; (6) U.S. Patent Application No. 11 / 228,758, filed on September 16, 2005, entitled “Virtual Input Device Placement On A Touch Screen User Interface”; (7) U.S. Patent Application No. 11 / 228,700, filed on September 16, 2005, entitled “Operation Of A Computer With A Touch Screen Interface”; (8) U.S. Patent Application No. 11 / 228,737, filed on September 16, 2005, entitled “Activating Virtual Keys Of A Touch-Screen Virtual Keyboard”; and (9) U.S. Patent Application No. 11 / 367,749, filed on March 3, 2006, entitled “Multi-Functional Hand-Held Device”. All of these applications are incorporated herein by reference in their entirety.

[0054] The touch screen 212 has, for example, a video resolution exceeding 100 dpi. In some embodiments, the touch screen has a video resolution of approximately 160 dpi. The user makes contact with the touch screen 212 using any suitable object or appendage, such as a stylus, a finger, or the like. In some embodiments, the user interface is designed to operate primarily through finger-based contacts and gestures, which may not be as precise as stylus-based input due to the larger contact area of ​​a finger on the touch screen. In some embodiments, the device converts rough finger-based input into precise pointer / cursor positions or commands for performing the user's desired action.

[0055] In some embodiments, in addition to the touch screen, the device 200 includes a touchpad (not shown) for activating or deactivating specific 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 the touch screen 212 or an extension of the touch-sensitive surface formed by the touch screen.

[0056] Device 200 also includes a power system 262 for powering the various components. Power system 262 includes a power management system, one or more power sources (e.g., batteries, alternating current (AC)), a recharging system, power fault detection circuitry, 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 a portable device.

[0057] Device 200 also includes one or more optical sensors 264 . Figure 2A An optical sensor coupled to the optical sensor controller 258 in the I / O subsystem 206 is shown. The optical sensor 264 includes a charge-coupled device (CCD) or complementary metal oxide semiconductor (CMOS) phototransistor. The optical sensor 264 receives light projected from the environment through one or more lenses and converts the light into data representing an image. In conjunction with the imaging module 243 (also called a camera module), the optical sensor 264 captures still images or video. In some embodiments, the optical sensor is located on the rear of the device 200, facing away from the touch screen display 212 on the front of the device, so that the touch screen display can be used as a viewfinder for still image and / or video image acquisition. In some embodiments, the optical sensor is located on the front of the device so that the user's image can be captured for video conferencing while viewing other video conference participants on the touch screen display. In some embodiments, the position of the optical sensor 264 can be changed by the user (for example, by rotating the lens and sensor in the device housing), so that a single optical sensor 264 can be used with the touch screen display for both video conferencing and still image and / or video image acquisition.

[0058] Device 200 optionally also includes one or more contact intensity sensors 265 . Figure 2A A contact force sensor is shown coupled to a force sensor controller 259 in the I / O subsystem 206. Contact force sensor 265 optionally includes one or more piezoresistive strain gauges, capacitive force sensors, electrical force sensors, piezoelectric force sensors, optical force sensors, capacitive touch-sensitive surfaces, or other force sensors (e.g., sensors for measuring the force (or pressure) of a contact on a touch-sensitive surface). Contact force sensor 265 receives contact force information (e.g., pressure information or a surrogate for pressure information) from the environment. In some embodiments, at least one contact force sensor is juxtaposed with or adjacent to a touch-sensitive surface (e.g., touch-sensitive display system 212). In some embodiments, at least one contact force sensor is located on the back of device 200, opposite to touch screen display 212 located on the front of device 200.

[0059] Device 200 also includes one or more proximity sensors 266 . Figure 2A A proximity sensor 266 is shown coupled to the peripherals interface 218. Alternatively, the proximity sensor 266 is coupled to the input controller 260 in the I / O subsystem 206. The proximity sensor 266 is implemented as described in the following U.S. patent applications: 11 / 241,839, entitled “Proximity Detector In Handheld Device,” 11 / 240,788, entitled “Proximity Detector In Handheld Device,” 11 / 620,702, entitled “Using Ambient Light Sensor To Augment Proximity Sensor Output,” 11 / 586,862, entitled “Automated Response To And Sensing Of User Activity In Portable Devices,” and 11 / 638,251, entitled “Methods And Systems For Automatic Configuration Of Peripherals,” which are hereby incorporated by reference in their entireties. In some embodiments, when the multifunction device is placed near the user's ear (e.g., when the user is on a phone call), the proximity sensor turns off and disables the touch screen 212.

[0060] Device 200 optionally also includes one or more tactile output generators 267 . Figure 2AA tactile output generator is shown coupled to a tactile feedback controller 261 in the I / O subsystem 206. The tactile output generator 267 optionally includes one or more electroacoustic devices such as speakers or other audio components; and / or electromechanical devices for converting energy into linear motion such as motors, solenoids, electroactive polymers, piezoelectric actuators, electrostatic actuators, or other tactile output generating components (e.g., components for converting electrical signals into tactile outputs on the device). The contact force sensor 265 receives tactile feedback generation instructions from the tactile feedback module 233 and generates tactile outputs on the device 200 that can be felt by a user of the device 200. In some embodiments, at least one tactile output generator is juxtaposed or adjacent to a touch-sensitive surface (e.g., touch-sensitive display system 212) and optionally generates tactile outputs by moving the touch-sensitive surface vertically (e.g., inward / outward toward the surface of the device 200) or laterally (e.g., back and forth in the same plane as the surface of the device 200). In some embodiments, at least one tactile output generator sensor is located on the back of the device 200, opposite the touch screen display 212 located on the front of the device 200.

[0061] Device 200 also includes one or more accelerometers 268 . Figure 2A An accelerometer 268 is shown coupled to the peripherals interface 218. Alternatively, the accelerometer 268 is coupled to the input controller 260 in the I / O subsystem 206. The accelerometer 268 implements as described in the following U.S. Patent Publication No. 20050190059, “Acceleration-based Theft Detection System for Portable Electronic Devices,” and U.S. Patent Publication No. 20060017692, “Methods And Apparatuses For Operating A Portable Device Based On An Accelerometer,” both of which are incorporated herein by reference in their entireties. In some embodiments, information is displayed in a portrait view or a landscape view on the touch screen display based on analysis of data received from one or more accelerometers. The device 200 optionally includes a magnetometer (not shown) and a GPS (or GLONASS or other global navigation system) receiver (not shown) in addition to the one or more accelerometers 268 for obtaining information about the position and orientation (e.g., portrait or landscape) of the device 200.

[0062] In some embodiments, the software components stored in memory 202 include an operating system 226, a communication module (or instruction set) 228, a contact / motion module (or instruction set) 230, a graphics module (or instruction set) 232, a text input module (or instruction set) 234, a global positioning system (GPS) module (or instruction set) 235, a digital assistant client module 229, and an application (or instruction set) 236. In addition, memory 202 stores data and models, such as user data and models 231. In addition, in some embodiments, memory 202 ( Figure 2A ) or 470( Figure 4 ) storage device / global internal state 257, such as Figure 2A and Figure 4 . The device / global internal state 257 includes one or more of the following: an active application state, which indicates which applications, if any, are currently active; a display state, which indicates what applications, views, or other information occupy various areas of the touch screen display 212; a sensor state, which includes information obtained from the device's various sensors and input control devices 216; and position information regarding the device's position and / or posture.

[0063] The 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 facilitating communication between various hardware components and software components.

[0064] The communication module 228 facilitates communication with other devices via one or more external ports 224 and also includes various software components for processing data received by the RF circuit 208 and / or the external ports 224. The external ports 224 (e.g., Universal Serial Bus (USB), FireWire, etc.) are suitable for coupling directly to other devices or indirectly through a network (e.g., the Internet, wireless LAN, etc.). In some embodiments, the external ports are connected to (trademark of Apple Inc.) devices.

[0065] The contact / motion module 230 optionally detects contact with the touch screen 212 (in conjunction with the display controller 256) and other touch-sensitive devices (e.g., a trackpad or physical click wheel). The contact / motion module 230 includes various software components for performing various operations related to contact detection, such as determining whether contact has occurred (e.g., detecting a finger down event), determining the strength of the contact (e.g., the force or pressure of the contact, or a surrogate for the force or pressure of the contact), determining whether there has been movement of the contact and tracking the movement on the touch-sensitive surface (e.g., detecting one or more finger drag events), and determining whether the contact has ceased (e.g., detecting a finger lift event or contact break). The contact / motion module 230 receives contact data from the touch-sensitive surface. Determining the movement of a contact point optionally includes determining the rate (magnitude), velocity (magnitude and direction), and / or acceleration (change in magnitude and / or direction) of the contact point, the movement of which is represented by a series of contact data. These operations are optionally applied to a single point of contact (e.g., a single-finger contact) or multiple points of contact simultaneously (e.g., "multi-touch" / multiple-finger contact). In some embodiments, the contact / motion module 230 and display controller 256 detect contact on the touchpad.

[0066] In some embodiments, the contact / motion module 230 uses a set of one or more intensity thresholds to determine whether an action has been performed by a user (e.g., to determine whether a user has "clicked" an icon). In some embodiments, at least a subset of the intensity thresholds are determined based on software parameters (e.g., the intensity thresholds are not determined by the activation thresholds of specific physical actuators and can be adjusted without changing the physical hardware of the device 200). For example, a mouse "click" threshold for a touchpad or touchscreen can be set to any one of a large range of predefined thresholds without changing the touchpad or touchscreen display hardware. In addition, in some embodiments, a software setting is provided to the user of the device for adjusting one or more intensity thresholds in a set of intensity thresholds (e.g., by adjusting individual intensity thresholds and / or by utilizing a system-level click on an "intensity" parameter to adjust multiple intensity thresholds at once).

[0067] The contact / motion module 230 optionally detects gesture input from the user. Different gestures on the touch-sensitive surface have different contact patterns (e.g., different motions, timings, and / or intensities of the detected contacts). Thus, gestures are optionally detected by detecting specific contact patterns. For example, detecting a finger tap gesture includes detecting a finger press event and then detecting a finger lift (lift-off) event at the same location (or substantially the same location) as the finger press event (e.g., at the location of an icon). As another example, detecting a finger swipe gesture on the touch-sensitive surface includes detecting a finger press event, then detecting one or more finger drag events, and then detecting a finger lift (lift-off) event.

[0068] The graphics module 232 includes various known software components for rendering and displaying graphics on the touch screen 212 or other display, including components for changing the visual impact (e.g., brightness, transparency, saturation, contrast, or other visual characteristics) of the displayed graphics. As used herein, the term "graphics" includes any object that can be displayed to a user, including, but not limited to, text, web pages, icons (such as user interface objects including soft keys), digital images, videos, animations, etc.

[0069] In some embodiments, the graphics module 232 stores data representing graphics to be used. Each graphic is optionally assigned a corresponding code. The graphics module 232 receives one or more codes specifying the graphics to be displayed from an application program or the like, along with coordinate data and other graphic attribute data, if necessary, and then generates screen image data for output to the display controller 256.

[0070] Haptic feedback module 233 includes various software components for generating instructions used by one or more tactile output generators 267 to produce tactile output at one or more locations on device 200 in response to user interaction with device 200 .

[0071] Text input module 234 , which in some examples is part of graphics module 232 , provides a soft keyboard for entering text in various applications (eg, contacts 237 , email 240 , IM 241 , browser 247 , and any other application requiring text input).

[0072] The GPS module 235 determines the location of the device and provides this information for use in various applications (e.g., to the phone 238 for use in location-based dialing; to the camera 243 as picture / video metadata; and to applications that provide location-based services, such as the weather widget, the local yellow pages widget, and the map / navigation widget).

[0073] The digital assistant client module 229 includes various client-side digital assistant instructions to provide client-side functionality of the digital assistant. For example, the digital assistant client module 229 is capable of accepting voice input (e.g., speech input), text input, touch input, and / or gesture input through various user interfaces of the portable multifunction device 200 (e.g., microphone 213, one or more accelerometers 268, touch-sensitive display system 212, one or more optical sensors 264, other input control devices 216, etc.). The digital assistant client module 229 is also capable of providing output in the form of audio (e.g., speech output), visual output, and / or tactile output through various output interfaces of the portable multifunction device 200 (e.g., speaker 211, touch-sensitive display system 212, one or more tactile output generators 267, etc.). For example, the output is provided as speech, sound, alarm, text message, menu, graphic, video, animation, vibration, and / or a combination of two or more of the above. During operation, the digital assistant client module 229 communicates with the DA server 106 using the RF circuit 208.

[0074] 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 items, shopping lists, etc.) to provide the client-side functionality of the digital assistant. In addition, user data and models 231 include various models for processing user input and determining user intent (e.g., speech recognition models, statistical language models, natural language processing models, knowledge ontologies, task flow models, service models, etc.).

[0075] In some examples, the digital assistant client module 229 utilizes the various sensors, subsystems, and peripherals of the portable multifunction device 200 to gather additional information from the environment surrounding the portable multifunction device 200 to establish a context associated with the user, the current user interaction, and / or the current user input. In some examples, the digital assistant client module 229 provides the context information, or a subset thereof, along with the user input to the DA server 106 to help infer user intent. In some examples, the digital assistant also uses the context information to determine how to prepare and transmit output to the user. The context information is referred to as context data.

[0076] In some examples, the contextual information accompanying the user input includes sensor information, such as lighting, ambient noise, ambient temperature, images or videos of the surrounding environment, etc. In some examples, the contextual information may also include the physical state of the device, such as device orientation, device location, device temperature, power level, speed, acceleration, motion pattern, cellular signal strength, etc. In some examples, information related to the software state of the DA server 106, such as the running process of the portable multifunction device 200, installed programs, past and current network activity, background services, error logs, resource usage, etc., is provided to the DA server 106 as contextual information associated with the user input.

[0077] In some examples, the digital assistant client module 229 selectively provides information stored on the portable multifunction device 200 (e.g., user data 231) in response to a request from the DA server 106. In some examples, the digital assistant client module 229 also elicits additional input from the user via a natural language dialog or other user interface upon request by the DA server 106. The digital assistant client module 229 transmits the additional input to the DA server 106 to assist the DA server 106 in inferring intent and / or fulfilling the user intent expressed in the user request.

[0078] Reference below 7A to 7C A more detailed description of the digital assistant is provided. It should be appreciated that the digital assistant client module 229 may include any number of submodules of the digital assistant module 726 described below.

[0079] The application 236 includes the following modules (or instruction sets) or a subset or superset thereof:

[0080] Contacts module 237 (sometimes called address book or contact list);

[0081] Telephone module 238;

[0082] Video conferencing module 239;

[0083] Email client module 240;

[0084] Instant messaging (IM) module 241;

[0085] Fitness support module 242;

[0086] A camera module 243 for still and / or video images;

[0087] Image management module 244;

[0088] Video player module;

[0089] Music player module;

[0090] Browser module 247;

[0091] Calendar module 248;

[0092] Widget module 249, which in some examples includes one or more of the following: weather widget 249-1, stock widget 249-2, calculator widget 249-3, alarm clock widget 249-4, dictionary widget 249-5, and other user-acquired widgets and user-created widgets 249-6;

[0093] A widget creator module 250 for forming user-created widgets 249-6;

[0094] Search module 251;

[0095] Video and music player module 252, which combines the video player module and the music player module;

[0096] Notepad module 253;

[0097] Map module 254; and / or

[0098] Online video module 255.

[0099] Examples of other applications 236 stored in memory 202 include other word processing applications, other image editing applications, drawing applications, rendering applications, JAVA-enabled applications, encryption, digital rights management, voice recognition, and voice reproduction.

[0100] In combination with the touch screen 212, display controller 256, touch / motion module 230, graphics module 232, and text input module 234, the contacts module 237 is used to manage an address book or contact list (for example, stored in the application internal state 292 of the contacts module 237 in memory 202 or memory 470), including: adding one or more names to the address book; deleting names from the address book; associating phone numbers, email addresses, physical addresses or other information with names; associating images with names; categorizing and classifying names; providing phone numbers or email addresses to initiate and / or facilitate communications via telephone 238, video conferencing module 239, email 240 or IM 241; and so on.

[0101] 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, phone module 238 is used to enter a character sequence corresponding to a phone number, access one or more phone numbers in contacts module 237, modify an already entered phone number, dial a corresponding phone number, conduct a conversation, and disconnect or hang up when the conversation is complete. As described above, wireless communications use any of a variety of communication standards, protocols, and technologies.

[0102] In combination with the RF circuit 208, the audio circuit 210, the speaker 211, the microphone 213, the touch screen 212, the display controller 256, the optical sensor 264, the optical sensor controller 258, the touch / motion module 230, the graphics module 232, the text input module 234, the contact module 237 and the telephone module 238, the video conferencing module 239 includes executable instructions for initiating, conducting and terminating a video conference between a user and one or more other participants in accordance with user instructions.

[0103] In conjunction with RF circuitry 208, touch screen 212, display controller 256, contact / motion module 230, graphics module 232, and text input module 234, email client module 240 includes executable instructions for creating, sending, receiving, and managing emails in response to user instructions. In conjunction with image management module 244, email client module 240 makes it very easy to create and send emails with still images or video images captured by camera module 243.

[0104] In combination with the RF circuit 208, the touch screen 212, the display controller 256, the contact / motion module 230, the graphics module 232, and the text input module 234, the instant messaging module 241 includes executable instructions for entering a character sequence corresponding to an instant message, modifying previously entered characters, transmitting the corresponding instant message (e.g., using the Short Message Service (SMS) or Multimedia Messaging Service (MMS) protocol for phone-based instant messaging or using XMPP, SIMPLE, or IMPS for Internet-based instant messaging), receiving instant messages, and viewing received instant messages. In some embodiments, the transmitted and / or received instant messages include graphics, photos, audio files, video files, and / or other attachments as supported in MMS and / or Enhanced Messaging Service (EMS). As used herein, "instant messaging" refers to both phone-based messages (e.g., messages sent using SMS or MMS) and Internet-based messages (e.g., messages sent using XMPP, SIMPLE, or IMPS).

[0105] In combination with the RF circuit 208, the touch screen 212, the display controller 256, the touch / motion module 230, the graphics module 232, the text input module 234, the GPS module 235, the map module 254, and the music player module, the fitness support module 242 includes executable instructions for: creating a workout (e.g., with time, distance, and / or calorie burn goals); communicating with fitness sensors (exercise equipment); receiving fitness sensor data; calibrating sensors for monitoring fitness; selecting and playing music for a workout; and displaying, storing, and transmitting fitness data.

[0106] In combination with the touch screen 212, the display controller 256, one or more optical sensors 264, the optical sensor controller 258, the touch / motion module 230, the graphics module 232, and the image management module 244, the camera module 243 includes executable instructions for capturing still images or videos (including video streams) and storing them in the memory 202, modifying the characteristics of the still images or videos, or deleting the still images or videos from the memory 202.

[0107] In conjunction with the touch screen 212, display controller 256, touch / motion module 230, graphics module 232, text input module 234, and camera module 243, the image management module 244 includes executable instructions for arranging, modifying (e.g., editing), or otherwise manipulating, labeling, deleting, presenting (e.g., in a digital slideshow or album), and storing still images and / or video images.

[0108] In combination with the RF circuit 208, the touch screen 212, the display controller 256, the touch / motion module 230, the graphics module 232 and the text input module 234, the browser module 247 includes executable instructions for browsing the Internet in accordance with user instructions, including searching for, linking to, receiving and displaying web pages or portions thereof, as well as attachments and other files linked to web pages.

[0109] In combination with the RF circuit 208, the touch screen 212, the display controller 256, the touch / motion module 230, the graphics module 232, the text input module 234, the email client module 240 and the browser module 247, the calendar module 248 includes executable instructions for creating, displaying, modifying and storing a calendar and data associated with the calendar (e.g., calendar entries, to-do items, etc.) in accordance with user instructions.

[0110] In combination with the RF circuit 208, the touch screen 212, the display controller 256, the contact / motion module 230, the graphics module 232, the text input module 234, and the browser module 247, the desktop widget module 249 is a mini-application that can be downloaded and used by a user (e.g., the weather desktop widget 249-1, the stock desktop widget 249-2, the calculator desktop widget 249-3, the alarm desktop widget 249-4, and the dictionary desktop widget 249-5) or a mini-application created by a user (e.g., the user-created desktop widget 249-6). In some embodiments, the desktop widget includes an HTML (Hypertext Markup Language) file, a CSS (Cascading Style Sheets) file, and a JavaScript file. In some embodiments, the desktop widget includes an XML (Extensible Markup Language) file and a JavaScript file (e.g., the Yahoo! desktop widget).

[0111] In combination with the RF circuit 208, the touch screen 212, the display controller 256, the touch / motion module 230, the graphics module 232, the text input module 234 and the browser module 247, the desktop widget creator module 250 is used by users to create desktop widgets (for example, to turn a user-specified portion of a web page into a desktop widget).

[0112] In combination with the touch screen 212, display controller 256, contact / motion module 230, graphics module 232 and text input module 234, the search module 251 includes executable instructions for searching the memory 202 for text, music, sound, images, videos and / or other files that match one or more search criteria (e.g., one or more user-specified search terms) in accordance with user instructions.

[0113] 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 a 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), as well as executable instructions for displaying, presenting, or otherwise playing back video (e.g., on touch screen 212 or on an external display connected 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.).

[0114] In conjunction with the touch screen 212, display controller 256, contact / motion module 230, graphics module 232 and text input module 234, the notepad module 253 includes executable instructions for creating and managing notes, to-do lists, etc. according to user instructions.

[0115] In combination with the RF circuit 208, the touch screen 212, the display controller 256, the touch / motion module 230, the graphics module 232, the text input module 234, the GPS module 235 and the browser module 247, the map module 254 is used to receive, display, modify and store maps and data associated with the maps (e.g., driving directions, data related to stores and other points of interest at or near a particular location, and other location-based data) in accordance with user instructions.

[0116] In conjunction with the touch screen 212, display controller 256, contact / motion module 230, graphics module 232, audio circuit 210, speaker 211, RF circuit 208, text input module 234, email client module 240, and browser module 247, the online video module 255 includes instructions that allow a user to access, browse, receive (e.g., by streaming and / or downloading), play back (e.g., on the touch screen or on a connected external display via external port 224), send an email with a link to a particular online video, and otherwise manage online videos in one or more file formats (e.g., H.264). In some embodiments, the instant messaging module 241 is used instead of the email client module 240 to send a link to a particular online video. Additional descriptions of online video applications can be found in U.S. Provisional Patent Application No. 60 / 936,562, filed on June 20, 2007, entitled “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” and U.S. Patent Application No. 11 / 968,067, filed on December 31, 2007, entitled “Portable Multifunction Device, Method, and Graphical User Interface for Playing Online Videos,” the contents of which are hereby incorporated by reference in their entirety.

[0117] Each of the modules and applications described above corresponds to an executable instruction set for performing one or more of the functions described above and the methods described in this patent application (e.g., the computer-implemented methods and other information processing methods described herein). These modules (e.g., instruction sets) do not have to be implemented as separate software programs, processes, or modules, and therefore various subsets of these modules may be combined or otherwise rearranged in various embodiments. For example, a video player module may be combined with a music player module into a single module (e.g., Figure 2AIn some embodiments, the memory 202 stores a subset of the above modules and data structures. In addition, the memory 202 stores additional modules and data structures not described above.

[0118] In some embodiments, the device 200 is a device in which the operation of a predefined set of functions on the device is performed exclusively through a touch screen and / or a touch pad. By using the touch screen and / or the touch pad as the primary input control device for the operation of the device 200, the number of physical input control devices (such as push buttons, dials, etc.) on the device 200 is reduced.

[0119] A predefined set of functions that are exclusively performed through the touch screen and / or trackpad optionally includes navigation between user interfaces. In some embodiments, the trackpad, when touched by the user, navigates the device 200 from any user interface displayed on the device 200 to a main menu, home menu, or root menu. In such embodiments, the trackpad is used to implement a "menu button." In some other embodiments, the menu button is a physical push button or other physical input control device, rather than a trackpad.

[0120] Figure 2B is a block diagram illustrating exemplary components for event processing according to some embodiments. In some embodiments, memory 202 ( Figure 2A ) or memory 470( Figure 4 ) includes an event classifier 270 (e.g., in the operating system 226) and a corresponding application 236-1 (e.g., any one of the aforementioned applications 237 to 251, 255, 480 to 490).

[0121] The event classifier 270 receives event information and determines the application 236-1 and the application view 291 of the application 236-1 to which the event information is to be delivered. The event classifier 270 includes an event monitor 271 and an event dispatcher module 274. In some embodiments, the application 236-1 includes an application internal state 292 that indicates one or more current application views that are displayed on the touch-sensitive display 212 when the application is active or executing. In some embodiments, the device / global internal state 257 is used by the event classifier 270 to determine which application(s) are currently active, and the application internal state 292 is used by the event classifier 270 to determine the application view 291 to which the event information is to be delivered.

[0122] In some embodiments, the application internal state 292 includes additional information, such as one or more of the following: resumption information to be used when the application 236-1 resumes execution, user interface state information indicating that information is being displayed or is ready to be displayed by the application 236-1, a state queue for enabling the user to return to a previous state or view of the application 236-1, and a repeat / undo queue of previous actions taken by the user.

[0123] Event monitor 271 receives event information from peripherals interface 218. The event information includes information about sub-events (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 sensors such as proximity sensor 266, one or more accelerometers 268, and / or microphone 213 (through audio circuit 210). The information that peripherals interface 218 receives from I / O subsystem 206 includes information from touch-sensitive display 212 or a touch-sensitive surface.

[0124] In some embodiments, event monitor 271 sends requests to peripheral device interface 218 at predetermined intervals. In response, peripheral device interface 218 transmits event information. In other embodiments, peripheral device interface 218 transmits event information only when there is a significant event (e.g., receiving an input above a predetermined noise threshold and / or receiving an input for more than a predetermined duration).

[0125] In some embodiments, the event classifier 270 also includes a hit view determination module 272 and / or an active event identifier determination module 273.

[0126] When the touch-sensitive display 212 displays more than one view, the hit view determination module 272 provides software procedures for determining where within one or more views a sub-event has occurred. A view consists of controls and other elements that a user can see on the display.

[0127] Another aspect of the user interface associated with an application is a set of views, sometimes also referred to herein as application views or user interface windows, in which information is displayed and touch-based gestures occur. The application views (of the respective application) in which a touch is detected correspond to a programmatic hierarchy of the application or a programmatic level within the view hierarchy. For example, the lowest-level view in which a touch is detected is called a hit view, and the set of events that are considered to be valid input is determined at least in part based on the hit view of the initial touch that started the touch-based gesture.

[0128] Hit view determination module 272 receives information related to sub-events of touch-based gestures. When an application has multiple views organized in a hierarchy, hit view determination module 272 identifies the hit view as the lowest view in the hierarchy where the sub-events should be processed. In most cases, the hit view is the lowest-level view in which the initiating sub-event (e.g., the first sub-event in a sequence of sub-events that form an event or potential event) occurs. Once a hit view is identified by 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.

[0129] Active event recognizer determination module 273 determines which view or views within the 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 the sub-event are actively participating views, and therefore determines that all actively participating views should receive a particular sequence of sub-events. In other embodiments, even if a touch sub-event is completely confined to an area associated with one particular view, views higher in the hierarchy will still remain actively participating views.

[0130] Event dispatcher module 274 dispatches event information to event recognizers (e.g., event recognizer 280). In embodiments that include active event recognizer determination module 273, event dispatcher module 274 delivers the event information to the event recognizer determined by active event recognizer determination module 273. In some embodiments, event dispatcher module 274 stores the event information in an event queue, which is retrieved by corresponding event receiver 282.

[0131] In some embodiments, operating system 226 includes event classifier 270. Alternatively, application 236-1 includes event classifier 270. In yet another embodiment, event classifier 270 is a standalone module or part of another module stored in memory 202, such as contact / motion module 230.

[0132] In some embodiments, application 236-1 includes multiple event handlers 290 and one or more application views 291, each of which includes instructions for handling touch events that occur within a corresponding view of the application's user interface. Each application view 291 of application 236-1 includes one or more event recognizers 280. Typically, the corresponding application view 291 includes multiple event recognizers 280. In other embodiments, one or more of the event recognizers 280 are part of a separate module, such as a user interface toolkit (not shown) or a higher-level object from which application 236-1 inherits methods and other properties. In some embodiments, the corresponding event handler 290 includes one or more of the following: a data updater 276, an object updater 277, a GUI updater 278, and / or event data 279 received from an event classifier 270. The event handler 290 utilizes or calls the data updater 276, the object updater 277, or the GUI updater 278 to update the application's internal state 292. Alternatively, one or more of the application views in the application views 291 include one or more corresponding event handlers 290. Additionally, in some embodiments, one or more of the data updater 276, object updater 277, and GUI updater 278 are included in the corresponding application view 291.

[0133] A corresponding event identifier 280 receives event information (e.g., event data 279) from event classifier 270 and identifies an event from the event information. Event identifier 280 includes an event receiver 282 and an event comparator 284. In some embodiments, event identifier 280 also includes metadata 283 and at least a subset of event delivery instructions 288 (which includes sub-event delivery instructions).

[0134] The event receiver 282 receives event information from the event classifier 270. The event information includes information about sub-events such as touches or touch movements. Depending on the sub-event, the event information also includes additional information, such as the location of the sub-event. When the sub-event involves the movement of a touch, the event information also includes the rate and direction of the sub-event. In some embodiments, the event includes the device rotating from one orientation to another (for example, from a portrait orientation to a landscape orientation, or vice versa), and the event information includes corresponding information about the current orientation of the device (also referred to as the device posture).

[0135] The event comparator 284 compares the event information with a predefined event or sub-event definition and, based on the comparison, determines the event or sub-event, or determines or updates the state of the event or sub-event. In some embodiments, the event comparator 284 includes an event definition 286. The event definition 286 includes a definition of an event (e.g., a predefined sequence of sub-events), such as event 1 (287-1), event 2 (287-2), and other events. In some embodiments, the sub-events in event (287) include, for example, touch start, touch end, touch move, touch cancel, and multi-touch. In one example, the definition of event 1 (287-1) is a double-click on a displayed object. For example, a double-click includes a first touch (touch start) of a predetermined duration on the displayed object, a first lift-off (touch end) of a predetermined duration, a second touch (touch start) of a predetermined duration on the displayed object, and a second lift-off (touch end) of a predetermined duration. In another example, the definition of event 2 (287-2) is a drag on a displayed object. For example, dragging includes a touch (or contact) of a predetermined duration on a displayed object, movement of the touch on the touch-sensitive display 212, and lifting of the touch (touch end). In some embodiments, the event also includes information for one or more associated event handlers 290.

[0136] In some embodiments, event definition 287 includes definitions of events for corresponding user interface objects. 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 displaying three user interface objects 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 corresponding 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 that is associated with the sub-event and the object that triggered the hit test.

[0137] In some embodiments, the definition of the corresponding event (287) also includes a delay action that delays the delivery of the event information until it has been determined that the sub-event sequence does or does not correspond to the event type of the event identifier.

[0138] When a corresponding event recognizer 280 determines that a sub-event sequence does not match any event in event definitions 286, the corresponding event recognizer 280 enters the event not possible, event failed, or event ended state, after which subsequent sub-events of the touch-based gesture are ignored. In this case, other event recognizers (if any) that remain active for the hit view continue to track and process sub-events of the ongoing touch-based gesture.

[0139] In some embodiments, the corresponding event recognizer 280 includes metadata 283 having configurable properties, flags, and / or lists that indicate how the event delivery system should perform sub-event delivery for actively participating event recognizers. In some embodiments, metadata 283 includes configurable properties, flags, and / or lists that indicate how event recognizers interact or can interact with each other. In some embodiments, metadata 283 includes configurable properties, flags, and / or lists that indicate whether sub-events are delivered to different levels in a view or programmatic hierarchy.

[0140] In some embodiments, when one or more specific sub-events of an event are identified, the corresponding event recognizer 280 activates the event handler 290 associated with the event. In some embodiments, the corresponding event recognizer 280 delivers event information associated with the event to the event handler 290. Activating the event handler 290 is different from sending (and deferred sending) the sub-events to the corresponding hit view. In some embodiments, the event recognizer 280 throws a flag associated with the identified event, and the event handler 290 associated with the flag obtains the flag and performs a predefined process.

[0141] 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 the event information to an event handler associated with the sub-event sequence or to an actively participating view. The event handler associated with the sub-event sequence or with the actively participating view receives the event information and performs a predetermined process.

[0142] In some embodiments, data updater 276 creates and updates data used in application 236-1. For example, data updater 276 updates phone numbers used in contact module 237 or stores video files 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 new user interface objects or updates the position of user interface objects. GUI updater 278 updates the GUI. For example, GUI updater 278 prepares display information and sends the display information to graphics module 232 for display on a touch-sensitive display.

[0143] In some embodiments, event handler 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 the corresponding application 236-1 or application view 291. In other embodiments, they are included in two or more software modules.

[0144] It should be understood that the above discussion of event handling for user touches on a touch-sensitive display also applies to other forms of user input utilizing input devices to operate the multifunction device 200, and not all user input is initiated on a touch screen. For example, mouse movement and mouse button presses, optionally in conjunction with single or multiple keyboard presses or holddowns; contact movement on a trackpad, such as taps, drags, scrolls, etc.; stylus input; movement of the device; spoken commands; detected eye movement; biometric input; and / or any combination thereof, are optionally used as input corresponding to sub-events defining the event to be recognized.

[0145] Figure 3A portable multifunction device 200 with a touch screen 212 is shown according to some embodiments. The touch screen optionally displays one or more graphics within a user interface (UI) 300. In this embodiment and other embodiments described below, a user can select one or more of the graphics by, for example, making gestures on the graphics using one or more fingers 302 (not drawn to scale in the figure) or one or more styluses 303 (not drawn to scale in the figure). In some embodiments, selection of the one or more graphics occurs when the user breaks contact with the one or more graphics. In some embodiments, the gesture optionally includes one or more taps, one or more swipes (from left to right, from right to left, up and / or down), and / or rolling of the finger that has made contact with the device 200 (from right to left, from left to right, up and / or down). In some embodiments or in some cases, inadvertent contact with a graphic does not select the graphic. For example, a swipe gesture that sweeps over an application icon optionally does not select the corresponding application when the gesture corresponding to selection is a tap.

[0146] The device 200 also includes one or more physical buttons, such as a "home" or menu button 304. As previously described, the menu button 304 is used to navigate to any application 236 in a set of applications executing on the device 200. Alternatively, in some embodiments, the menu button is implemented as a soft key in a GUI displayed on the touch screen 212.

[0147] In some embodiments, the device 200 includes a touch screen 212, a menu button 304, a push button 306 for powering the device on / off and for locking the device, one or more volume adjustment buttons 308, a subscriber identity module (SIM) card slot 310, a headset jack 312, and a docking / charging external port 224. The push button 306 is optionally used to turn the device on / off by pressing the button and holding it in the depressed state for a predefined time interval; to lock the device by pressing the button and releasing it before the predefined time interval has elapsed; and / or to unlock the device or initiate an unlocking process. In an alternative embodiment, the device 200 also accepts speech input for activating or deactivating certain functions via the microphone 213. The device 200 also optionally includes one or more contact force sensors 265 for detecting the intensity of contact on the touch screen 212, and / or one or more tactile output generators 267 for generating tactile output for the user of the device 200.

[0148] Figure 44 is a block diagram of an exemplary multifunction device with a display and a touch-sensitive surface according to some embodiments. The device 400 does not have to be portable. In some embodiments, the device 400 is a laptop computer, a desktop computer, a tablet computer, a multimedia player device, a navigation device, an educational device (such as a children's learning toy), a gaming system, or a control device (e.g., a home controller or an industrial controller). The device 400 typically includes one or more processing units (CPUs) 410, one or more network or other communication interfaces 460, a memory 470, and one or more communication buses 420 for interconnecting these components. The communication bus 420 optionally includes circuits (sometimes referred to as a chipset) that interconnect system components and control communications between system components. The device 400 includes an input / output (I / O) interface 430 with a display 440, which is typically a touch screen display. The I / O interface 430 also optionally includes a keyboard and / or mouse (or other pointing device) 450 and a touchpad 455, a tactile output generator 457 for generating tactile output on the device 400 (e.g., similar to the above referenced device). Figure 2A The one or more tactile output generators 267 described above), sensors 459 (e.g., optical sensors, acceleration sensors, proximity sensors, touch sensors, and / or contact intensity sensors (similar to those described above with reference to Figure 2A The one or more contact intensity sensors 265 described herein)). Memory 470 includes high-speed random access memory, such as DRAM, SRAM, DDR RAM, or other random access solid-state memory devices; and optionally includes non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. Memory 470 optionally includes one or more storage devices located remotely from CPU 410. In some embodiments, memory 470 stores data related to portable multifunction device 200 ( Figure 2A ) or a subset thereof. In addition, memory 470 optionally stores additional programs, modules, and data structures not present in memory 202 of portable multifunction device 200. For example, memory 470 of device 400 optionally stores a drawing module 480, a presentation module 482, a word processing module 484, a website creation module 486, a disk editing module 488, and / or a spreadsheet module 490, while portable multifunction device 200( Figure 2A )'s memory 202 optionally does not store these modules.

[0149] Figure 4Each of the above-mentioned elements in some examples is stored in one or more previously mentioned memory devices. Each module in the above-mentioned modules corresponds to an instruction set for performing the above-mentioned functions. The above-mentioned modules or programs (e.g., instruction sets) do not have to be implemented as independent software programs, processes or modules, so the various subsets of these modules are combined or otherwise rearranged in various embodiments. In some embodiments, memory 470 stores a subset of the above-mentioned modules and data structures. In addition, memory 470 stores additional modules and data structures not described above.

[0150] Attention is now turned to embodiments of a user interface that may be implemented on, for example, portable multifunction device 200 .

[0151] Figure 5A An exemplary user interface for an applications menu on portable multifunction device 200 is shown according to some embodiments. A similar user interface is implemented on device 400. In some embodiments, user interface 500 includes the following elements, or a subset or superset thereof:

[0152] one or more signal strength indicators 502 of one or more wireless communications such as cellular signals and Wi-Fi signals;

[0153] Time 504;

[0154] Bluetooth indicator 505;

[0155] Battery status indicator 506;

[0156] A tray 508 with icons for commonly used applications, such as:

[0157] o An icon 516 labeled "Phone" for the phone module 238, which optionally includes an indicator 514 of the number of missed calls or voice messages;

[0158] o An icon 518 labeled "Mail" of the email client module 240, which optionally includes an indicator 510 of the number of unread emails;

[0159] o An icon 520 labeled "Browser" for the browser module 247; and

[0160] ○ Video and music player module 252 (also known as iPod (trademark of Apple Inc.)

[0161] module 252) and an icon 522 labeled "iPod"; and

[0162] Icons for other apps, such as:

[0163] o Icon 524 labeled "Messages" of the IM module 241;

[0164] o Icon 526 labeled "Calendar" of the calendar module 248;

[0165] o Icon 528 labeled "Photos" of the image management module 244;

[0166] o An icon 530 labeled “Camera” of the camera module 243;

[0167] ○ Icon 532 labeled “Online Video” of the online video module 255;

[0168] ○ Icon 534 labeled “Stock Market” of the Stock Market widget 249-2;

[0169] o Icon 536 labeled "Map" of the map module 254;

[0170] ○ Icon 538 labeled “Weather” of weather widget 249-1;

[0171] ○ Icon 540 labeled “Clock” of the alarm clock widget 249-4;

[0172] o An icon 542 labeled “Fitness Support” of the fitness support module 242;

[0173] o An icon 544 labeled "Notepad" of the Notepad module 253; and

[0174] o An icon 546 labeled “Settings” for a settings application or module that provides access to settings for the device 200 and its various applications 236 .

[0175] It should be pointed out that Figure 5A The icon labels shown in are exemplary only. For example, icon 522 for video and music player module 252 is optionally labeled "Music" or "Music Player." Other labels are optionally used for various application icons. In some embodiments, the label of a respective application icon includes the name of the application corresponding to the respective application icon. In some embodiments, the label of a particular application icon is different from the name of the application corresponding to the particular application icon.

[0176] Figure 5B A touch-sensitive surface 551 (eg, touch screen display 212) is shown having a touch-sensitive surface 551 (eg, touch screen display 212) that is separate from a display 550 (eg, touch screen display 212). Figure 4 tablet or touchpad 455) of the device (e.g., Figure 4Device 400 also optionally includes one or more contact intensity sensors (e.g., one or more sensors among sensors 459) for detecting intensity of contacts on touch-sensitive surface 551 and / or a tactile output generator or multiple tactile output generators 457 for generating tactile output for a user of device 400.

[0177] Although some of the examples that follow will be given with reference to input on a touch screen display 212 (where a touch-sensitive surface and a display are combined), in some embodiments, the device detects input on a touch-sensitive surface that is separate from the display, such as Figure 5B In some embodiments, the touch-sensitive surface (e.g., Figure 5B 551) has a main axis (e.g., Figure 5B 553) corresponding to the main axis (for example, Figure 5B According to these embodiments, the device detects a position corresponding to a corresponding position on the display (e.g., Figure 5B , 560 corresponds to 568 and 562 corresponds to 570 ) at contact with touch-sensitive surface 551 (e.g., Figure 5B 560 and 562 in ). Thus, on a touch-sensitive surface (e.g., Figure 5B 551) and a display of a multi-function device (e.g., Figure 5B When the user input detected by the device on the touch-sensitive surface (e.g., contacts 560 and 562 and their movement) is separated, the device is used to manipulate the user interface on the display. It should be understood that similar methods are optionally used for other user interfaces described herein.

[0178] In addition, although the following examples are primarily given with reference to finger inputs (e.g., finger contacts, single-finger tap gestures, finger swipe gestures), it should be understood that in some embodiments, one or more of these finger inputs are replaced by input from another input device (e.g., mouse-based input or stylus input). For example, a swipe gesture is optionally replaced by a mouse click (e.g., instead of contact), followed by movement of the cursor along the path of the swipe (e.g., instead of movement of the contact). For another example, a tap gesture is optionally replaced by a mouse click when the cursor is over the location of the tap gesture (e.g., instead of detecting the contact, followed by ceasing to detect the contact). Similarly, when multiple user inputs are detected simultaneously, it should be understood that multiple computer mice are optionally used simultaneously, or mice and finger contacts are optionally used simultaneously.

[0179] Figure 6AAn exemplary personal electronic device 600 is shown. The device 600 includes a body 602. In some embodiments, the device 600 includes a body 602 relative to the devices 200 and 400 (e.g., Figures 2A-4 ) some or all of the features described in . In some embodiments, device 600 has a touch-sensitive display screen 604, referred to hereinafter as touch screen 604. As an alternative to or in addition to touch screen 604, device 600 has a display and a touch-sensitive surface. As is the case with devices 200 and 400, in some embodiments, touch screen 604 (or touch-sensitive surface) has one or more intensity sensors for detecting the intensity of contact (e.g., a touch) being applied. The one or more intensity sensors of touch screen 604 (or touch-sensitive surface) provide output data representing the intensity of the touch. The user interface of device 600 responds to touches based on the intensity of the touch, which means that touches of different intensities can invoke different user interface operations on device 600.

[0180] Technology for detecting and processing touch intensity may be found, for example, in related applications: International patent application serial number PCT / US2013 / 040061, entitled “Device, Method, and Graphical User Interface for Displaying UserInterface Objects Corresponding to an Application,” filed on May 8, 2013, and International patent application serial number PCT / US2013 / 069483, entitled “Device, Method, and Graphical UserInterface for Transitioning Between Touch Input to Display OutputRelationships,” filed on November 11, 2013, each of which is hereby incorporated by reference in its entirety.

[0181] In some embodiments, the 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, the device 600 has one or more attachment mechanisms. Such attachment mechanisms (if included) can allow the device 600 to be attached to, for example, hats, glasses, earrings, necklaces, shirts, jackets, bracelets, watchbands, wristbands, pants, belts, shoes, wallets, backpacks, etc. These attachment mechanisms allow the user to wear the device 600.

[0182] Figure 6BAn exemplary personal electronic device 600 is shown. In some embodiments, the device 600 includes a Figure 2A 、 Figure 2B and Figure 4 Some or all of the components described. The device 600 has a bus 612 that operatively couples an I / O portion 614 to one or more computer processors 616 and a memory 618. The I / O portion 614 is connected to a display 604, which may have a touch-sensitive component 622 and, optionally, a touch intensity-sensitive component 624. In addition, the I / O portion 614 is connected to a communication unit 630 for receiving application and operating system data using Wi-Fi, Bluetooth, near-field communication (NFC), cellular, and / or other wireless communication technologies. The device 600 includes input mechanisms 606 and / or 608. For example, the input mechanism 606 is a rotatable input device or a depressible input device and a rotatable input device. In some examples, the input mechanism 608 is a button.

[0183] In some examples, input mechanism 608 is a microphone. Personal electronic device 600 includes, for example, various sensors such as a GPS sensor 632, an accelerometer 634, an orientation sensor 640 (e.g., a compass), a gyroscope 636, a motion sensor 638, and / or combinations thereof, all of which are operatively connected to I / O portion 614.

[0184] The memory 618 of the personal electronic device 600 is a non-transitory computer-readable storage medium for storing computer-executable instructions that, when executed by one or more computer processors 616, cause the computer processors to perform the techniques and processes described above. The computer-executable instructions are also stored and / or transmitted, for example, within any non-transitory computer-readable storage medium for use by or in conjunction with an instruction execution system, apparatus, or device, such as a computer-based system, a system containing a processor, or other system that can obtain instructions from an instruction execution system, apparatus, or device and execute the instructions. The personal electronic device 600 is not limited to Figure 6B components and configurations, but may include other components or additional components in a variety of configurations.

[0185] As used herein, the term "indicator" refers to, for example, a display on device 200, 400, and / or 600 ( Figure 2A 、 Figure 4 and Figures 6A to 6B ) is a user-interactive graphical user interface object displayed on a display screen of a computer. For example, an image (e.g., an icon), a button, and text (e.g., a hyperlink) each constitute an affordance.

[0186] As used herein, the term "focus selector" refers to an input element used to indicate the current portion of a user interface with which a user is interacting. In some implementations that include a cursor or other position marker, the cursor acts as a "focus selector" such that when the cursor is over a particular user interface element (e.g., a button, window, slider, or other user interface element), a focus selector is displayed on a touch-sensitive surface (e.g., Figure 4 Touchpad 455 or Figure 5B In the event that an input (e.g., a press input) is detected on the touch-sensitive surface 551 in FIG, the particular user interface element is adjusted according to the detected input. In the case of a touch screen display (e.g., a touch screen display) that enables direct interaction with user interface elements on the touch screen display Figure 2A touch-sensitive display system 212 or Figure 5A In some implementations of the touch screen 212 in FIG, 20 , a contact detected on the touch screen acts as a “focus selector” such that when input (e.g., a press input by the contact) is detected at the location of a particular user interface element (e.g., a button, window, slider, or other user interface element) on the touch screen display, the particular user interface element is adjusted according to the detected input. In some implementations, the focus moves from one area of ​​the user interface to another area of ​​the user interface without corresponding movement of a cursor or movement of a contact on the touch screen display (e.g., by using a tab key or arrow keys to move the focus from one button to another); in these implementations, the focus selector moves according to the movement of the focus between different areas of the user interface. Regardless of the specific form the focus selector takes, the focus selector is generally a user interface element (or contact on the touch screen display) that is controlled by the user to deliver the user's intended interaction with the user interface (e.g., by indicating to the device the element of the user interface with which the user desires to interact). For example, when a press input is detected on a touch-sensitive surface (e.g., a trackpad or touch screen), the position of a focus selector (e.g., a cursor, contact, or selection box) over a corresponding button will indicate that the user intends to activate the corresponding button (rather than other user interface elements shown on the device display).

[0187] 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 seconds, 0.1 seconds, 0.2 seconds, 0.5 seconds, 1 second, 2 seconds, 5 seconds, 10 seconds) relative to a predefined event (e.g., after contact is detected, before contact is detected to be lifted off, before or after contact begins to move, before contact ends, before or after contact is detected to increase in intensity, and / or before or after contact is detected to decrease in intensity). The characteristic intensity of a contact is optionally based on one or more of the following: the maximum value of the contact intensity, the mean value of the contact intensity, the average value of the contact intensity, the value at the top 10% of the contact intensity, the half-maximum value of the contact intensity, the 90% maximum value of the contact intensity, etc. In some embodiments, the duration of the contact is used in determining the characteristic intensity (e.g., when the characteristic intensity is the average value of the intensity of the contact over time). In some embodiments, the feature strength is compared to a set of one or more strength thresholds to determine whether the user has performed an operation. For example, the set of one or more strength thresholds includes a first strength threshold and a second strength threshold. In this example, a contact whose feature strength does not exceed the first threshold results in a first operation, a contact whose feature strength exceeds the first strength threshold but does not exceed the second strength threshold results in a second operation, and a contact whose feature strength exceeds the second threshold results in a third operation. In some embodiments, a comparison between the feature strength and one or more thresholds is used to determine whether to perform one or more operations (e.g., whether to perform the corresponding operation or to abandon the corresponding operation), rather than to determine whether to perform the first operation or the second operation.

[0188] In some embodiments, a portion of a gesture is identified for use in determining the characteristic strength. For example, a touch-sensitive surface receives a continuous swipe contact that transitions from a starting position and reaches an ending position where the strength of the contact increases. In this example, the characteristic strength of the contact at the ending position is based only on a portion of the continuous swipe contact, rather than the entire swipe contact (e.g., the portion of the swipe contact that is located only at the ending position). In some embodiments, a smoothing algorithm is applied to the strength of the swipe contact before determining the characteristic strength of the contact. For example, the smoothing algorithm optionally includes one or more of the following: an unweighted sliding average smoothing algorithm, a triangular smoothing algorithm, a median filter smoothing algorithm, and / or an exponential smoothing algorithm. In some cases, these smoothing algorithms eliminate narrow peaks or dips in the strength of the swipe contact to achieve the purpose of determining the characteristic strength.

[0189] 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 an operation typically associated with clicking a button of a physical mouse or trackpad. In some embodiments, the deep press intensity threshold corresponds to an intensity at which the device will perform an operation different from the operation typically associated with clicking a button of a physical mouse or 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, contacts below the nominal contact detection intensity threshold are no longer detected), the device will move the focus selector in accordance with the 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 speaking, unless otherwise stated, these intensity thresholds are consistent between different groups of user interface illustrations.

[0190] An increase in contact feature intensity from an intensity below a 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 in contact feature intensity from an intensity below a deep press intensity threshold to an intensity above the deep press intensity threshold is sometimes referred to as a "deep press" input. An increase in contact feature intensity from an intensity below a 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 a contact on the touch surface. A decrease in contact feature intensity from an intensity above the contact detection intensity threshold to an intensity below the contact detection intensity threshold is sometimes referred to as detecting a contact lifted 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.

[0191] In some embodiments described herein, one or more operations are performed in response to detecting a gesture that includes a corresponding press input or in response to detecting a corresponding press input performed using a corresponding contact (or multiple contacts), wherein the corresponding press input is detected at least in part based on detecting an increase in the intensity of the contact (or multiple contacts) to above a press input intensity threshold. In some embodiments, the corresponding operation is performed in response to detecting an increase in the intensity of the corresponding contact to above the press input intensity threshold (e.g., a "down stroke" of the corresponding press input). In some embodiments, the press input includes an increase in the intensity of the corresponding contact to above the press input intensity threshold and a subsequent decrease in the intensity of the contact to below the press input intensity threshold, and the corresponding operation is performed in response to detecting a subsequent decrease in the intensity of the corresponding contact to below the press input threshold (e.g., an "up stroke" of the corresponding press input).

[0192] In some embodiments, the device employs intensity hysteresis to avoid unexpected inputs, sometimes referred to as "jitter," where the device defines or selects a hysteresis intensity threshold that has a predefined relationship to a 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, a press input includes an increase in the intensity of the corresponding contact to above the press input intensity threshold and a subsequent decrease in the intensity of the contact to below a hysteresis intensity threshold corresponding to the press input intensity threshold, and a corresponding operation is performed in response to detecting that the intensity of the corresponding contact subsequently decreases to below the hysteresis intensity threshold (e.g., an "upstroke" of the corresponding press input). Similarly, in some embodiments, a press input is detected only when the device detects that the contact intensity increases from an intensity equal to or below the hysteresis intensity threshold to an intensity equal to or above the press input intensity threshold and, optionally, that the contact intensity subsequently decreases to an intensity equal to or below the hysteresis intensity, and a corresponding operation is performed in response to detecting the press input (e.g., an increase in contact intensity or a decrease in contact intensity, depending on the circumstances).

[0193] For ease of explanation, a description of an operation performed in response to a press input associated with a press input intensity threshold or in response to a gesture including a press input is optionally triggered in response to detecting any of the following: contact intensity increasing above the press input intensity threshold, contact intensity increasing from an intensity below a hysteresis intensity threshold to an intensity above the press input intensity threshold, contact intensity decreasing below the press input intensity threshold, and / or contact intensity decreasing below a 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 that the intensity of the contact decreases below the press input intensity threshold, the operation is optionally performed in response to detecting that the intensity of the contact decreases below a hysteresis intensity threshold that corresponds to and is less than the press input intensity threshold.

[0194] 3. Digital Assistant System

[0195] Figure 7A A block diagram of a digital assistant system 700 according to various examples is shown. In some examples, the digital assistant system 700 is implemented on a stand-alone computer system. In some examples, the digital assistant system 700 is distributed across multiple computers. In some examples, some of the modules and functions of the digital assistant are divided into a server portion and a client portion, where the client portion is located on one or more user devices (e.g., device 104, device 122, device 200, device 400, or device 600) and communicates with the server portion (e.g., server system 108) over one or more networks, such as Figure 1 In some examples, the digital assistant system 700 is Figure 1 It should be noted that the digital assistant system 700 is only one example of a digital assistant system, and that the digital assistant system 700 may have more or fewer components than shown, combine two or more components, or have a different configuration or arrangement of components. Figure 7A The various components shown in the drawings are implemented in hardware, software instructions for execution by one or more processors, firmware (including one or more signal processing integrated circuits and / or application specific integrated circuits), or a combination thereof.

[0196] The digital assistant system 700 includes a memory 702, an input / output (I / O) interface 706, a network communication interface 708, and one or more processors 704. These components can communicate with each other via one or more communication buses or signal lines 710.

[0197] In some examples, memory 702 includes non-transitory computer-readable media, such as high-speed random access memory and / or non-volatile computer-readable storage media (e.g., one or more disk storage devices, flash memory devices, or other non-volatile solid-state memory devices).

[0198] In some examples, the I / O interface 706 couples the input / output devices 716 of the digital assistant system 700, such as a display, keyboard, touch screen, and microphone, to the user interface module 722. The I / O interface 706, together with the user interface module 722, receives user input (e.g., voice input, keyboard input, touch input, etc.) and processes the input accordingly. In some examples, such as when the digital assistant is implemented on a stand-alone user device, the digital assistant system 700 includes a plurality of interfaces with respect to the user interface module 722. Figure 2A 、 Figure 4 、 Figures 6A to 6B In some examples, digital assistant system 700 represents the server portion of a digital assistant implementation and can interact with a user through a client-side portion located on a user device (e.g., device 104, device 200, device 400, or device 600).

[0199] In some examples, the network communication interface 708 includes one or more wired communication ports 712 and / or wireless transmission and reception circuitry 714. The one or more wired communication ports receive and send communication signals via one or more wired interfaces such as Ethernet, Universal Serial Bus (USB), FIREWIRE, etc. The wireless circuitry 714 receives RF signals and / or optical signals from a communication network and other communication devices and sends RF signals and / or optical signals to a communication network and other communication devices. Wireless communication uses any of a variety of communication standards, protocols, and technologies, such as GSM, EDGE, CDMA, TDMA, Bluetooth, Wi-Fi, VoIP, Wi-MAX, or any other suitable communication protocol. The network communication interface 708 enables communication between the digital assistant system 700 and other devices over a network, 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).

[0200] In some examples, the memory 702 or the computer-readable storage medium of the memory 702 stores programs, modules, instructions, and data structures, including all or a subset of the following: operating system 718, communication module 720, user interface module 722, one or more application programs 724, and digital assistant module 726. Specifically, the memory 702 or the computer-readable storage medium of the memory 702 stores instructions for performing the above-described processes. The one or more processors 704 execute these programs, modules, and instructions and read data from or write data to the data structures.

[0201] The 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 communication between various hardware, firmware, and software components.

[0202] The communication module 720 facilitates communication between the digital assistant system 700 and other devices via the network communication interface 708. For example, the communication module 720 facilitates communication between the digital assistant system 700 and other devices (such as Figure 2A 、 Figure 4 、 Figures 6A to 6B The communication module 720 also includes various components for processing data received by the wireless circuit 714 and / or the wired communication port 712.

[0203] The user interface module 722 receives commands and / or input from the user (e.g., from a keyboard, touch screen, pointing device, controller, and / or microphone) via the I / O interface 706 and generates user interface objects on the display. The user interface module 722 also prepares output (e.g., speech, sound, animation, text, icons, vibration, tactile feedback, lighting, etc.) and transmits it to the user via the I / O interface 706 (e.g., through a display, audio channel, speaker, touchpad, etc.).

[0204] Applications 724 include programs and / or modules configured to be executed by the 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, calendar applications, navigation applications, or email applications. If the digital assistant system 700 is implemented on a server, applications 724 include, for example, resource management applications, diagnostic applications, or scheduling applications.

[0205] The memory 702 also stores a digital assistant module 726 (or the server portion of the digital assistant). In some examples, the digital assistant module 726 includes the following submodules, or subsets or supersets thereof: an input / output processing module 728, a speech-to-text (STT) processing module 730, a natural language processing module 732, a dialog flow processing module 734, a task flow processing module 736, a service processing module 738, and a 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 subsets or supersets thereof: a knowledge ontology 760, a vocabulary index 744, user data 748, a task flow model 754, a service model 756, and an ASR system 758.

[0206] In some examples, using the processing modules, data, and models implemented in the digital assistant module 726, the digital assistant may perform at least some of the following: convert speech input into text; recognize user intent expressed in natural language input received from the user; proactively elicit and obtain information needed to fully infer user intent (e.g., by disambiguating words, games, intents, etc.); determine a task flow for satisfying the inferred intent; and execute the task flow to satisfy the inferred intent.

[0207] In some examples, such as Figure 7B As shown in FIG, the I / O processing module 728 can be Figure 7A The I / O devices 716 in the Figure 7AThe network communication interface 708 in interacts with a user device (e.g., device 104, device 200, device 400, or device 600) to obtain user input (e.g., voice input) and provide a response to the user input (e.g., as voice output). The I / O processing module 728 optionally obtains context information associated with the user input from the user device along with or shortly after receiving the user input. The context information includes user-specific data, vocabulary, and / or preferences related to the user input. In some examples, the context information also includes the software state and hardware state of the user device at the time the user request is received, and / or information related to the user's surrounding environment at the time the user request is received. In some examples, the I / O processing module 728 also sends follow-up questions related to the user request to the user and receives answers from the user. When the user request is received by the I / O processing module 728 and the user request includes voice input, the I / O processing module 728 forwards the voice input to the STT processing module 730 (or speech recognizer) for speech-to-text conversion.

[0208] The STT processing module 730 includes one or more ASR systems 758. The one or more ASR systems 758 can process the speech input received by the I / O processing module 728 to generate recognition results. Each ASR system 758 includes a front-end speech preprocessor. The front-end speech preprocessor extracts representative features from the speech input. For example, the front-end speech preprocessor performs a Fourier transform on the speech input to extract spectral features that characterize the speech input as a sequence of representative multidimensional vectors. In addition, 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 engines based on dynamic time warping and engines based on weighted finite state transformers (WFST). One or more speech recognition models and one or more speech recognition engines are used to process the extracted representative features of the front-end speech preprocessor to produce intermediate recognition results (e.g., phonemes, phoneme strings, and sub-words), and ultimately produce text recognition results (e.g., words, word strings, or symbol sequences). In some examples, the voice input is at least partially processed by a third-party service or processed on the user's device (e.g., device 104, device 200, device 400, or device 600) to produce recognition results. Once the STT processing module 730 generates a recognition result containing a text string (e.g., a word, or a sequence of words, or a sequence of symbols), the recognition result is transmitted to the natural language processing module 732 for intention inference. In some examples, the STT processing module 730 generates multiple candidate text representations of the voice input. Each candidate text representation is a sequence of words or symbols corresponding to the voice input. In some examples, each candidate text representation is associated with a voice recognition confidence score. Based on the speech recognition confidence score, the STT processing module 730 ranks the candidate text representations and provides the n best (e.g., the n highest ranked) candidate text representations to the natural language processing module 732 for intent inference, where n is a predetermined integer greater than zero. For example, in one example, only the highest ranked (n=1) candidate text representation is delivered to the natural language processing module 732 for intent inference. For another example, the five highest ranked (n=5) candidate text representations are delivered to the natural language processing module 732 for intent inference.

[0209] More details regarding speech-to-text processing are described in U.S. Utility Patent Application Serial No. 13 / 236,942, filed on September 20, 2011, entitled “Consolidating Speech Recognition Results,” the entire disclosure of which is incorporated herein by reference.

[0210] In some examples, the STT processing module 730 includes a vocabulary of recognizable words and / or accesses the vocabulary via the phonetic alphabet conversion module 731. Each vocabulary word is associated with one or more candidate pronunciations of the word represented in the speech recognition phonetic alphabet. Specifically, the vocabulary of recognizable words includes words associated with multiple candidate pronunciations. For example, the vocabulary includes words associated with and In some examples, the candidate pronunciations for a word 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, for example, based on a known standard pronunciation.

[0211] In some examples, candidate pronunciations are ranked based on their prevalence. For example, Ranked higher than Because the former is the more common pronunciation (e.g., among all users, for users in a particular geographic region, or for any other suitable subset of users). In some examples, candidate pronunciations are ranked based on whether they are custom candidate pronunciations associated with the user. For example, custom candidate pronunciations are ranked higher than standard candidate pronunciations. This can be used to identify proper nouns that have unique pronunciations that deviate from the standard pronunciation. In some examples, candidate pronunciations are associated with one or more phonetic features such as geographic origin, country, or ethnicity. For example, a candidate pronunciation associated with the United States, while the candidate pronunciation Associated with the United Kingdom. In addition, the ranking of the candidate pronunciations is based on one or more characteristics of the user (e.g., geographic origin, country, race, etc.) in a user profile stored on the device. For example, it may be determined from the user profile that the user is associated with the United States. Based on the user being associated with the United States, the candidate pronunciations are ranked (Associated with the United States) Comparable candidate pronunciations (associated with the United Kingdom) is ranked higher. In some examples, one of the ranked candidate pronunciations may be selected as the predicted pronunciation (e.g., the most likely pronunciation).

[0212] When speech input is received, the STT processing module 730 is used to determine (e.g., using an acoustic model) a phoneme corresponding to the speech input and then attempts to determine (e.g., using a language model) a word that matches the phoneme. For example, if the STT processing module 730 first identifies a phoneme sequence corresponding to a portion of the speech input It may then determine based on the lexical index 744 that the sequence corresponds to the word "tomato".

[0213] In some examples, the STT processing module 730 uses fuzzy matching techniques to determine words in an utterance. Thus, for example, the STT processing module 730 determines the phoneme sequence corresponds to the word "tomato", even though this particular phoneme sequence is not a candidate phoneme sequence for that word.

[0214] The digital assistant's natural language processing module 732 ("natural language processor") takes the n best candidate text representations ("word sequences" or "symbol sequences") generated by the STT processing module 730 and attempts to associate each candidate text representation with one or more "executable intents" recognized by the digital assistant. An "executable intent" (or "user intent") represents a task that can be executed by the digital assistant and that can have an associated task flow implemented in the task flow model 754. The associated task flow is a series of programmed actions and steps that the digital assistant takes to perform the task. The scope of the digital assistant's capabilities depends on the number and variety of task flows that have been implemented and stored in the task flow model 754, or in other words, on the number and variety of "executable intents" recognized by the digital assistant. However, the effectiveness of the digital assistant also depends on the assistant's ability to infer the correct "one or more executable intents" from user requests expressed in natural language.

[0215] In some examples, in addition to the sequence of words or symbols obtained from the STT processing module 730, the natural language processing module 732 also receives contextual information associated with the user request, for example, from the I / O processing module 728. The natural language processing module 732 optionally uses the contextual information to clarify, supplement, and / or further qualify the information included in the candidate text representation received from the STT processing module 730. The contextual information includes, for example, user preferences, the hardware and / or software state of the user's device, sensor information collected before, during, or shortly after the user's request, previous interactions (e.g., conversations) between the digital assistant and the user, and the like. As described herein, in some examples, the contextual information is dynamic and changes with the time, location, content, and other factors of the conversation.

[0216] In some examples, natural language processing is based on, for example, a knowledge ontology 760. The knowledge ontology 760 is a hierarchical structure comprising many nodes, each node representing an "executable intent" or an "attribute" related to one or more of an "executable intent" or other "attributes". As described above, an "executable intent" represents a task that the digital assistant can perform, that is, the task is "executable" or can be performed. An "attribute" represents a parameter associated with a sub-aspect of an executable intent or another attribute. The connection between the executable intent node and the attribute node in the knowledge ontology 760 defines how the parameters represented by the attribute node are subordinate to the task represented by the executable intent node.

[0217] In some examples, the knowledge ontology 760 is composed of executable intent nodes and attribute nodes. Within the knowledge ontology 760, each executable intent node is directly connected to or connected to one or more attribute nodes through one or more intermediate attribute nodes. Similarly, each attribute node is directly connected to or connected to one or more executable intent nodes through one or more intermediate attribute nodes. For example, Figure 7C As shown, the knowledge ontology 760 includes a "restaurant reservation" node (i.e., an executable intent node). The attribute nodes "restaurant", "date / time" (for reservations), and "party size" are all directly connected to the executable intent node (i.e., the "restaurant reservation" node).

[0218] In addition, the attribute nodes "cuisine", "price range", "telephone number" and "location" are child nodes of the attribute node "restaurant", and are all connected to the "restaurant reservation" node (i.e., executable intent node) through the intermediate attribute node "restaurant". Figure 7C As shown, ontology 760 also includes a "Set Reminder" node (i.e., another executable intent node). The attribute nodes "Date / Time" (for setting reminders) and "Subject" (for reminders) are both connected to the "Set Reminder" node. Since the attribute "Date / Time" is related to both the task of making a restaurant reservation and the task of setting a reminder, the attribute node "Date / Time" is connected to both the "Restaurant Reservation" node and the "Set Reminder" node in ontology 760.

[0219] Executable intent nodes, along with their linked attribute nodes, are described as "domains". In this discussion, each domain is associated with a corresponding executable intent and refers to a set of nodes (and the relationships between these nodes) associated with a particular executable intent. For example, Figure 7CThe knowledge ontology 760 shown in includes an example of a restaurant reservation domain 762 and an example of a reminder domain 764 within the knowledge ontology 760. The restaurant reservation domain includes an executable intent node "restaurant reservation", attribute nodes "restaurant", "date / time" and "party size", and child attribute nodes "cuisine", "price range", "phone number" and "location". The reminder domain 764 includes an executable intent node "set reminder" and attribute nodes "subject" and "date / time". In some examples, the knowledge ontology 760 is composed of multiple domains. Each domain shares one or more attribute nodes with one or more other domains. For example, in addition to the restaurant reservation domain 762 and the reminder domain 764, the "date / time" attribute node is also associated with many different domains (e.g., a scheduling domain, a travel booking domain, a movie ticket domain, etc.).

[0220] although Figure 7C Two exemplary domains within the knowledge ontology 760 are shown, but other domains include, for example, "find a movie," "make a phone call," "find directions," "schedule a meeting," "send a message," and "provide answers to questions," "read a list," "provide navigation instructions," "provide instructions for a task," and the like. The "send message" domain is associated with the "send message" executable intent node and further includes attribute nodes such as "one or more recipients," "message type," and "message body." The attribute node "recipients" is further defined by, for example, child attribute nodes such as "recipient name" and "message address."

[0221] In some examples, ontology 760 includes all domains (and thus executable intents) that the digital assistant can understand and act upon. In some examples, ontology 760 is modified, such as by adding or removing entire domains or nodes, or by modifying the relationships between nodes within ontology 760.

[0222] In some examples, nodes associated with multiple related executable intents are clustered under a "superdomain" in the knowledge ontology 760. For example, the "travel" superdomain includes a cluster of attribute nodes and executable intent nodes related to travel. The executable intent nodes related to travel include "book an airline ticket", "book a hotel", "rent a car", "get directions", "find points of interest", etc. The executable intent nodes under the same superdomain (e.g., the "travel" superdomain) have multiple common attribute nodes. For example, the executable intent nodes for "book an airline ticket", "book a hotel", "rent a car", "get directions", and "find points of interest" share one or more of the attribute nodes "starting location", "destination", "departure date / time", "arrival date / time", and "number of people in the party".

[0223] In some examples, each node in the knowledge ontology 760 is associated with a set of words and / or phrases related to the attribute or executable intent represented by the node. The corresponding set of words and / or phrases associated with each node is called the "vocabulary" associated with the node. The corresponding set of words and / or phrases associated with each node is stored in the vocabulary index 744 associated with the attribute or executable intent represented by the node. For example, return Figure 7B For example, the vocabulary associated with the node for the "restaurant" attribute includes words such as "food," "drinks," "cuisine," "hunger," "eat," "pizza," "fast food," "meal," etc. For another example, the vocabulary associated with the node for the "make phone call" executable intent includes words and phrases such as "call," "make a phone call," "dial," "talk to," "call the number," "call," etc. The vocabulary index 744 optionally includes words and phrases in different languages.

[0224] The natural language processing module 732 receives candidate text representations (e.g., one or more text strings or one or more symbol sequences) from the STT processing module 730 and, for each candidate representation, determines which nodes the words in the candidate text representation refer to. In some examples, if a word or phrase in the candidate text representation is found (via the vocabulary index 744) to be associated with one or more nodes in the knowledge ontology 760, the word or phrase "triggers" or "activates" those nodes. Based on the number and / or relative importance of the activated nodes, the natural language processing module 732 selects one of the executable intents as the task that the user intends the digital assistant to perform. In some examples, the domain with the most "triggered" nodes is selected. In some examples, the domain with the highest confidence (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 importance of the triggered nodes. In some examples, additional factors are also considered in the process of selecting the node, such as whether the digital assistant has previously correctly interpreted a similar request from the user.

[0225] User data 748 includes user-specific information such as user-specific vocabulary, user preferences, user address, user's default second language, user's contact list, and other short-term or long-term information about each user. In some examples, natural language processing module 732 uses user-specific information to supplement the information contained in the user input to further define the user's intent. For example, in response to a user request to "invite my friends to my birthday party," natural language processing module 732 can access user data 748 to determine who "friends" are and when and where the "birthday party" will be held, without requiring the user to explicitly provide such information in their request.

[0226] It should be recognized that in some examples, the natural language processing module 732 is implemented using one or more machine learning mechanisms (e.g., neural networks). Specifically, the one or more machine learning mechanisms are configured to receive candidate text representations and context information associated with the candidate text representations. Based on the candidate text representations and the associated context information, the one or more machine learning mechanisms are configured to determine an intent confidence score based on a set of candidate executable intents. The natural language processing module 732 may select one or more candidate executable intents from a set of candidate executable intents based on the determined intent confidence scores. In some examples, a knowledge ontology (e.g., knowledge ontology 760) is also utilized to select one or more candidate executable intents from a set of candidate executable intents.

[0227] Additional details of searching ontologies based on symbolic strings are described in U.S. Utility Patent Application Serial No. 12 / 341,743, filed on December 22, 2008, entitled “Method and Apparatus for Searching Using An Active Ontology,” the entire disclosure of which is incorporated herein by reference.

[0228] In some examples, once the natural language processing module 732 identifies an executable intent (or domain) based on the user request, the natural language processing module 732 generates a structured query representing the identified executable intent. In some examples, the structured query includes parameters for one or more nodes within the executable intent's domain, and at least some of the parameters are populated with specific information and requirements specified in the user request. For example, a user may say, "Make me a reservation at a sushi restaurant for 7 p.m." In this case, the natural language processing module 732 is able to correctly identify the executable intent as "restaurant reservation" based on the user input. According to the knowledge ontology, a structured query for the "restaurant reservation" domain includes parameters such as {cuisine}, {time}, {date}, {number of people in the party}, etc. In some examples, based on the voice input and text derived from the voice input using the STT processing module 730, the 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 p.m."}. However, in this example, the user utterance does not contain sufficient information to complete the structured query associated with the domain. Therefore, based on the currently available information, other necessary parameters such as {number of people in the party} and {date} are not specified in the structured query. In some examples, the natural language processing module 732 populates some parameters of the structured query with the received contextual information. For example, in some examples, if the user requests a sushi restaurant "nearby," the natural language processing module 732 populates the {location} parameter in the structured query with the GPS coordinates from the user's device.

[0229] In some examples, the natural language processing module 732 identifies multiple candidate executable intents for each candidate text representation received from the STT processing module 730. In addition, in some examples, a corresponding structured query is generated (partially or fully) for each identified candidate executable intent. The natural language processing module 732 determines an intent confidence score for each candidate executable intent and ranks the candidate executable intents based on the intent confidence score. In some examples, the natural language processing module 732 transmits the generated one or more structured queries (including any completed parameters) to the task flow processing module 736 ("task flow processor"). In some examples, one or more structured queries for the m best (e.g., the m highest ranked) candidate executable intents are provided to the task flow processing module 736, where m is a predetermined integer greater than zero. In some examples, one or more structured queries for the m best candidate executable intents are provided to the task flow processing module 736 along with the corresponding one or more candidate text representations.

[0230] Additional details for inferring user intent based on multiple candidate executable intents determined based on multiple candidate textual representations of speech input are described in U.S. utility patent application serial number 14 / 298,725, entitled “System and Method for Inferring User Intent From Speech Inputs,” filed on June 6, 2014, the entire disclosure of which is incorporated herein by reference.

[0231] The task flow processing module 736 is configured to receive one or more structured queries from the natural language processing module 732, complete the structured queries (if necessary), and perform the actions required to "complete" the user's final request. In some examples, the various processes necessary to complete these tasks are provided in the task flow model 754. In some examples, the task flow model 754 includes a process for obtaining additional information from the user, as well as a task flow for performing actions associated with the executable intent.

[0232] As described above, to complete a structured query, the task flow processing module 736 may need to initiate additional conversations with the user to obtain additional information and / or clarify potentially ambiguous utterances. When such interaction is necessary, the task flow processing module 736 invokes the dialog flow processing module 734 to participate in the conversation with the user. In some examples, the dialog flow processing module 734 determines how (and / or when) to request additional information from the user and receives and processes user responses. Questions are presented to the user and responses are received from the user via I / O processing module 728. In some examples, the dialog flow processing module 734 presents the dialog output to the user via audible and / or visual output and receives input from the user via verbal or physical (e.g., click) responses. Continuing with the above example, when the task flow processing module 736 invokes the dialog flow processing module 734 to determine the "party size" and "date" information for the structured query associated with the domain "restaurant reservation," the dialog flow processing module 734 generates questions such as "How many people are in your party?" and "What day do you want to reserve a reservation?" and transmits them to the user. Once the answer is received from the user, the dialog flow processing module 734 fills the structured query with the missing information, or passes the information to the task flow processing module 736 to complete the missing information based on the structured query.

[0233] Once the task flow processing module 736 has completed the structured query for the executable intent, the task flow processing module 736 begins to execute the final task associated with the executable intent. Therefore, the 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 executable intent "restaurant reservation" includes steps and instructions for contacting a restaurant and actually requesting a reservation for a specific party size at a specific time. For example, using a structured query such as: {restaurant reservation, restaurant = ABC Cafe, date = 3 / 12 / 2012, time = 7pm, party size = 5}, the task flow processing module 736 may perform the following steps: (1) Log into the server of ABC Cafe or such A restaurant reservation system, (2) entering date, time, and party size information into a form on the website, (3) submitting the form, and (4) making a calendar entry for the reservation in the user's calendar.

[0234] In some examples, the task flow processing module 736, with the assistance of the service processing module 738 ("service processing module"), completes the task requested in the user input or provides the informational answer requested in the user input. For example, the service processing module 738 initiates a phone call, sets a calendar entry, invokes a map search, invokes or interacts with other user applications installed on the user device, and invokes or interacts with third-party services (e.g., a restaurant reservation portal, a social networking site, a bank portal, etc.) on behalf of the task flow processing module 736. In some examples, the protocols and application programming interfaces (APIs) required for each service are specified by the corresponding service model in the service model 756. The service processing module 738 accesses the appropriate service model for the service and generates a request for the service based on the protocol and API required by the service according to the service model.

[0235] For example, if a restaurant has enabled an online reservation service, the restaurant submits a service model that specifies the necessary parameters for making a reservation and transmits the values ​​of the necessary parameters to the API of the online reservation service. When requested by the task flow processing module 736, the service processing module 738 can use the web address stored in the service model to establish a network connection with the online reservation service and send the necessary parameters for 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.

[0236] In some examples, the natural language processing module 732, the dialogue flow processing module 734, and the task flow processing module 736 are used together and repeatedly to infer and define the user's intention, obtain information to further clarify and refine the user's intention, and ultimately generate a response (i.e., output to the user, or complete the task) to satisfy the user's intention. The generated response is a dialogue response to the voice input that at least partially satisfies the user's intention. In addition, in some examples, the generated response is output as a voice output. In these examples, the generated response is sent to the speech synthesis processing module 740 (e.g., a speech synthesizer), where the generated response can be processed to synthesize the dialogue response in the form of speech. In other examples, the generated response is data content related to satisfying the user request in the voice input.

[0237] In an example where the task flow processing module 736 receives multiple structured queries from the natural language processing module 732, the task flow processing module 736 first processes the first structured query of the received structured queries in an attempt to complete the first structured query and / or perform one or more tasks or actions represented by the first structured query. In some examples, the first structured query corresponds to the highest-ranked executable intent. In other examples, the first structured query is selected from the structured queries received based on a combination of the corresponding speech recognition confidence score and the corresponding intent confidence score. In some examples, if the task flow processing module 736 encounters an error during processing of the first structured query (e.g., due to an inability to determine the necessary parameters), the task flow processing module 736 may continue to select and process a second structured query corresponding to a lower-ranked executable intent in the received structured queries. For example, the second structured query is selected based on the speech recognition confidence score of the corresponding candidate text representation, the intent confidence score of the corresponding candidate executable intent, the missing necessary parameters in the first structured query, or any combination thereof.

[0238] The speech synthesis processing module 740 is configured to synthesize speech output for presentation to the user. The speech synthesis processing module 740 synthesizes speech output based on the text provided by the digital assistant. For example, the generated dialogue response is in the form of a text string. The speech synthesis processing module 740 converts the text string into audible speech output. The speech synthesis processing module 740 uses any appropriate speech synthesis technology to generate speech output from the text, including but not limited to: concatenative synthesis, unit selection synthesis, diphone synthesis, domain-specific synthesis, formant synthesis, pronunciation synthesis, Hidden Markov Model (HMM)-based synthesis, and sine wave synthesis. In some examples, the speech synthesis processing module 740 is configured to synthesize individual words based on phoneme strings corresponding to these words. For example, the phoneme strings are associated with the words in the generated dialogue response. The phoneme strings are stored in metadata associated with the words. The speech synthesis processing module 740 is configured to directly process the phoneme strings in the metadata to synthesize the words in speech form.

[0239] In some examples, instead of using the speech synthesis processing module 740 (or in addition), speech synthesis is performed on a remote device (e.g., server system 108), and the synthesized speech is sent to the user device for output to the user. For example, this may occur in some implementations where the output of the digital assistant is generated at the server system. And because the server system typically has more processing power or more resources than the user device, it is possible to obtain higher quality speech output than client-side synthesis would achieve.

[0240] Additional details about digital assistants can be found in U.S. utility patent application No. 12 / 987,982, filed on January 10, 2011, entitled “Intelligent Automated Assistant,” and U.S. utility patent application No. 13 / 251,088, filed on September 30, 2011, entitled “Generating and Processing Task Items That Represent Tasks to Perform,” the entire disclosures of which are incorporated herein by reference.

[0241] 4. Multi-state digital assistants for continuous conversations

[0242] Figures 8 and 9 A system and process for continuing a conversation with a digital assistant at an electronic device is shown. For example, the electronic device may include any device described herein, including but not limited to device 104, device 200, device 400, and device 600 ( Figure 1 、 Figure 2A 、 Figure 4 and Figures 6A to 6B ). Therefore, it should be understood that Figures 8 and 9 The associated electronic devices may correspond to any type of user device, such as a phone, laptop, desktop computer, tablet, wearable device (e.g., smartwatch, head-mounted display, etc.), home speaker, etc. Furthermore, the processes described herein may be performed by a server with information delivered to and from the device, executed on the device, or a combination thereof.

[0243] Typically, a first voice input 802 may be received from a user, such as a voice input comprising a trigger phrase followed by a command. For example, a user may say “Hey, Siri, what’s the weather like?” to query current weather conditions (e.g., the weather associated with the current location). In response to receiving the first voice input, the digital assistant may provide a response 804 to the user, such as “It’s 70 degrees and sunny” with reference to, for example, one or more weather databases. Specifically, a text representation of the output may be obtained using the weather database, such that TTS processing is performed on the text to provide a voice output to the user. Display output corresponding to the text representation may also be performed in conjunction with or in place of the voice output (e.g., including a banner with a “sun” icon at “70°”).

[0244] Typically, a first output is provided, corresponding to the digital assistant in a first state. The first output may include a display output and / or an audio output. For example, the digital assistant object may be displayed in various states to provide interaction details to the user. These states may indicate the digital assistant state to the user, such as the level of attention the digital assistant is providing to the user, the amount of information the digital assistant is gathering, the amount of processing resources being used, and the like. For example, once the response 804 is provided (e.g., the audio output ends), the digital assistant object is displayed on the electronic device's display in the first state. The digital assistant object may be displayed as having a first size and a first animation profile (e.g., a round sphere with slowly rotating lights and a particular set of colors). For example, the first state may indicate that the digital assistant is actively listening for subsequent voice input from the user. While the digital assistant object is displayed, the user may provide a second voice input 808. The second voice input 808 may correspond to a subsequent voice input or a voice input that is otherwise related to the first voice input 802 and / or the response 804. For example, using the first voice input 802 and the response 804 as context, a user may say, "How's Seattle?" to implicitly request weather conditions in Seattle.

[0245] In some examples, the first output may include a sound output. For example, the first output may include a sound signal (e.g., a prompt tone or a soft tone) indicating that the digital assistant object is transitioning or has transitioned to the first state. The sound output may be instantaneous or may be continuous. For example, the first sound output may begin with a prompt tone or a soft tone, and then soft ambient audio may be played for the duration that the digital assistant remains in the first state (or for a shorter duration). The sound output may be provided at one or more speakers of the electronic device, or may be provided via an auxiliary electronic device (e.g., a wired or wireless headset connected to the device). For example, a user may be using a home speaker system or may be using a smartphone device connected to wireless headsets.

[0246] Various values ​​and other signals can be used to determine whether the additional speech is directed at the digital assistant. Specifically, once the digital assistant transitions to the first state, a first plurality of values ​​806 is obtained. As described herein, the first plurality of values ​​806 can be used to determine a first confidence level corresponding to the second speech input 808. Typically, obtaining the first plurality of values ​​can be based on whether the electronic device is configured for echo cancellation. Specifically, a device configured for echo cancellation may include functionality that immediately begins collecting and analyzing the first plurality of values ​​(and / or other values) after the user completes the request to provide a response. When this functionality is enabled, the user can interrupt the digital assistant once it begins providing a response. For example, the user may utter the first phrase, "What's the weather like in Cupertino?" In response, the digital assistant may begin outputting the response, "It's sunny..." For example, the response may include text-to-speech (TTS) output, allowing the user to interrupt the digital assistant while providing a response. Specifically, the user may interrupt the digital assistant's response with a subsequent utterance, "Sorry, I meant San Francisco." When using a device with echo cancellation enabled, the first plurality of values ​​806 is collected and analyzed immediately after the user finishes uttering the first phrase. Thus, in the case of an echo cancellation-enabled device, any vocal response from the digital assistant can be detected and considered for use of echo cancellation, while the device can begin analyzing any subsequent speech and related signals immediately after the user completes providing the initial input. Thus, obtaining the first plurality of values ​​is initiated in response to detecting the end of the first speech input 802, based on a determination that the electronic device is configured for echo cancellation. Alternatively, obtaining the first plurality of values ​​is initiated in response to detecting the end of the provided response 804, based on a determination that the electronic device is not configured for echo cancellation.

[0247] The first plurality of values ​​806 may be analyzed to determine and / or adjust a first confidence level. The first confidence level may correspond to a degree of confidence regarding whether the additional speech is directed to the digital assistant. Specifically, upon detecting a minimum threshold duration 810 of speech (e.g., 500 milliseconds of speech), a determination is made as to whether each value in the first plurality of values ​​806 satisfies at least one rule, as described herein. If the minimum threshold duration 810 is detected, a determination is made as to whether the corresponding value in the plurality of values ​​806 satisfies at least one rule. Based on determining that the corresponding value satisfies at least one rule, the first confidence level is increased. Similarly, based on determining that the corresponding value does not satisfy at least one rule, the first confidence level is decreased. In some examples, based on determining that the corresponding value does not satisfy at least one rule, the first confidence level is maintained without adjustment. In other words, the confidence level may be dynamically adjusted based on the corresponding value and the associated rules.

[0248] Typically, the first plurality of values ​​806 may be based on various signals related to user gaze, user lip movement, user's relative attention, device location information, voice detection, and the like. As discussed herein, the various values ​​may also not be used for user privacy. For example, a user may choose not to provide gaze or lip movement information, or may provide such information only in limited circumstances. In some examples, voice detection is typically used (e.g., using a voice detector on the device). Specifically, a value indicating that user voice is being detected at the electronic device may be obtained. In this case, a first confidence level is increased based on determining that the voice value satisfies a voice rule (e.g., user voice is being detected). In some examples, user gaze directed at a display of the electronic device is detected, such as determining whether the user's gaze is directed at a displayed digital assistant object. For example, the user may be looking at the displayed digital assistant object before and / or while speaking the second voice input 808. Thus, a gaze value indicating that the user is looking at the digital assistant object may be obtained. In this case, a first confidence level is increased based on determining that the gaze value satisfies a gaze rule (e.g., the user's gaze must be directed at the digital assistant object). In some examples, the user's lip movement is detected and a corresponding value is obtained based on the lip movement. For example, the lip movement value may correspond to one or more of a lip movement duration, lip features (e.g., mouth appearance, face orientation), a viseme associated with the lip movement, etc. In this case, based on determining that the lip movement value satisfies the lip movement rule, a first confidence level is increased. For example, the recognized viseme may correspond to a sound associated with the second speech input 808, and / or a particular lip movement duration may correspond to a particular portion of the speech duration (e.g., duration 810).

[0249] In some examples, a general direction associated with the user's gaze is detected. For example, a value is obtained based on determining that the user's gaze is generally directed toward a display of an electronic device. In this case, a first confidence level is increased based on determining that the gaze direction value satisfies a gaze direction rule (e.g., the user's gaze is directed toward the device display). Specifically, this value can be utilized if the user is not looking at the digital assistant object but is generally still using the electronic device. In some examples, the location information can be associated with device location, device orientation, and / or device acceleration information, such as changes in device location, orientation, and / or acceleration. For example, for example. The user may raise the device to a position substantially close to the user's face immediately before and / or while speaking the second voice input 808. Thus, a location value indicating that the relevant device is raised can be obtained. In this case, a first confidence level is increased based on determining that the location value satisfies a location rule (e.g., the device is raised before and / or during the voice input).

[0250] Typically, the first confidence level can be compared to a threshold confidence level. The comparison can occur dynamically as the confidence level is adjusted, or can occur at one or more specific times. For example, determination 812 can include a comparison of the first confidence level to a first confidence level threshold. Determination 812 can occur after a minimum threshold duration 810 of voice detection. Based on determining that the first confidence level exceeds the first threshold confidence level, a second output corresponding to the digital assistant in the second state is provided. The second state can include displaying a digital assistant object and / or providing a sound output. For example, a digital assistant object having a second size and a second animation profile can be displayed. The second size can be larger than the first size associated with the first display state. In addition, the second animation profile can include an indication that the device is actively sampling user voice input in order to recognize a command. For example, a digital assistant object in the second state can include a circular sphere with rotating light (e.g., the light rotates faster than in the first state) and a specific color set (e.g., more vivid than the light in the first state). The digital assistant object in the second state can also include fluctuations in the size of the digital assistant object based on the amplitude of the detected voice. When the digital assistant object is displayed in the second state, the electronic device can continue to receive the second voice input.

[0251] In some examples, a second sound output is provided to indicate that the digital assistant has transitioned or is transitioning to a second state. For example, a first sound output (e.g., a soft beep or subtle tone) may be provided to indicate that the digital assistant object is in the first state, while a second sound output different from the first sound output (e.g., a louder beep, a longer tone, etc.) may be provided to indicate that the digital assistant has transitioned to the second state. A continuous ambient noise (or noise of a predetermined duration) may also be provided, such as a second continuous tone that is different from the first continuous tone provided during the first state.

[0252] return Figure 8 , a second plurality of values ​​814 may also be obtained based on determining that the first confidence level exceeds the first threshold confidence level at step 812. In a subsequent step, a second confidence level corresponding to the second speech input 808 is obtained. The second confidence level may be based on, for example, the first plurality of values ​​806 and the second plurality of values ​​814 determined at step 816. Typically, the second plurality of values ​​814 may be based on additional signals indicating whether the user speech is intended for the digital assistant. Specifically, these signals and corresponding values ​​may be associated with device processes having higher or more robust processing capabilities than the first plurality of signals, such as determinations involving speaker identity, user intent, neural networks, etc.

[0253] In some examples, a predetermined duration of speech is analyzed to identify a user intent associated with the speech, such as an intent involving accessing information from a digital assistant in the form of a question (e.g., based on detection of the word "how"). The intent can be determined based on identification of an ontology node corresponding to a corresponding feasible intent. Thus, the intent value included in the second plurality of values ​​814 can correspond to the determined intent. In this case, a second confidence level is increased based on a determination that the intent value satisfies an intent rule (e.g., the intent must be associated with a user request of the digital assistant). In some examples, speech recognition is performed. Specifically, a first speaker profile and a second speaker profile are obtained associated with the first speech input 802 and the second speech input 808. Speaker profiles generally identify various characteristics of speech, such as pitch, tone, rhythm, prosody, meter, etc. Based on a comparison of the speaker profiles (e.g., comparing one or more features or a combination of features), a speaker identification value is obtained and included in the second plurality of values ​​814. In this case, a second confidence level is increased based on a determination that the speaker identification value satisfies a speaker identification rule (e.g., the speaker profiles match or are otherwise sufficiently similar based on a similarity threshold).

[0254] In some examples, a recurrent neural network (RNN) is utilized to obtain a representation of user intent based on an embedding of speech input. Typically, a lattice embedding can be obtained based on speech recognition output (e.g., from an automatic speech recognition component). The lattice embedding can be generated by using speech recognition as input to the RNN and obtaining the lattice embedding as output. The user intent can then be derived based on the lattice embedding to obtain an RNN intent value as a value of the second plurality of values ​​814. In this case, a second confidence level is increased based on determining that the RNN intent value satisfies the RNN intent rule (e.g., the intent obtained from the lattice embedding must be associated with the user's request to the digital assistant).

[0255] Once the second confidence level is obtained at step 816, the second confidence level is compared to a second threshold confidence level, for example during a mitigation voting process 818. Obtaining the confidence levels and performing the mitigation voting process may be based at least in part on a rule-oriented framework and / or may be based at least in part on a data learning model. For example, various values ​​may be weighted higher than other values ​​and therefore may influence the final confidence value more than other values. For example, a user gaze value (associated with whether the user is looking at the digital assistant object) may be weighted higher than a lip movement value. Methods using data learning models may also utilize data from previous user interactions to inform the model how to weight the various values. For example, if previous interaction data indicates that the user's gaze at the digital assistant generally corresponds to speech directed at the digital assistant, the weight of the corresponding user gaze value (from the first plurality of values ​​806) may be increased. Additional variables may also be considered during the mitigation voting process 818. For example, the duration between the response 804 (e.g., the beginning of the response 804, the middle of the response 804, the end of the response 804, etc.) and the start of the second voice input 808 may affect the outcome of the mitigation voting process 818. Specifically, a shorter duration between the response 804 and the second voice input 808 may result in an adjustment to the second confidence level, such as an increase.

[0256] Typically, changes in various values ​​throughout the interaction process can provide contextual information that can be used to adjust or otherwise influence confidence levels. For example, when the user provides the first voice input 802, a first gaze pattern may be detected. When the user provides the second voice input 808, a second gaze pattern may be detected. Changes between the first gaze pattern and the second gaze pattern may affect various confidence levels. For example, the first gaze pattern may indicate that the user is generally looking in the direction of the device or its surroundings, while the second gaze pattern may indicate that the user is looking at the digital assistant object while speaking the entire second voice input 808. Based on the change in the gaze pattern from general attention to high attention, the second confidence value may be increased. Other changes may also affect various confidence values. For example, when the device is placed on a surface (e.g., a smartphone placed on a table), the user may initially interact with the digital assistant. When the user speaks the subsequent voice input, the user may have raised the device to view or otherwise speak more directly to the device. Changes in device motion, including raising the device, may increase various confidence levels, such as the second confidence level. Changes in various acoustic parameters, RNN outputs, and other user attention values ​​(e.g., changes between one or more different inputs / outputs) may cause confidence values ​​to increase or decrease based on the corresponding changes.

[0257] The first plurality of values ​​and the second plurality of values ​​may be dynamically updated and / or updated based on various factors. Specifically, a result candidate may be identified based on characteristics of the second voice input 808. The result candidate may correspond to a specific word in the voice input (e.g., "how," "about," or "Seattle"), a specific portion of a word, a duration of speech, etc. In response to identifying the result candidate, an updated first plurality of values ​​806 and an updated second plurality of values ​​814 are obtained, for example, at step 820. Thus, at step 820, an updated second confidence level is obtained based on the updated first and second plurality of values. The updated second confidence level may then be compared to a second threshold confidence level during the mitigation voting process 822.

[0258] Typically, based on determining that the second confidence level exceeds a second threshold confidence level (e.g., at step 818), the second voice input continues to be received. Specifically, given a sufficiently high confidence that the user voice is directed to the digital assistant, the digital assistant remains in the second state and continues to receive the user voice. Alternatively, based on determining that the second confidence level does not exceed a second threshold confidence level (e.g., at step 822), the second voice input is stopped. Here, the confidence level reflects a sufficiently low confidence that the voice is directed to the digital assistant, and therefore, the digital assistant exits the second state (e.g., returns to an idle or lower power state).

[0259] Now refer to Figure 9 As another example, it may be determined that the first confidence level does not exceed a first threshold confidence level. Specifically, a user may provide voice input 902 to an electronic device regarding a weather query, and in response to receiving voice input 902, the digital assistant may provide a response 904 to the user (e.g., "It's 70 degrees and sunny"). Here, the electronic device may not be able to detect the user's gaze (e.g., a home speaker, wireless headphones, etc.). In another example, the user may provide voice input 902 to an electronic device that is capable of detecting the user's gaze, even though the user may be positioned such that the camera and other optical sensors on the device cannot capture any facial features of the user. Thus, it may be determined that various values ​​in the first plurality of values ​​906 do not satisfy corresponding rules. Specifically, the gaze value may not satisfy the rule that the user must be looking at the digital assistant object, the gaze direction value may not satisfy the rule that the user must be at least approximately looking at the display of the electronic device, and / or the lip movement value may not satisfy the rule that the user's lip movement must correspond to the user's speech. Based on one or more of the corresponding values ​​that do not satisfy the corresponding rules, it is determined that the first confidence level does not exceed the first threshold confidence level.

[0260] Based on determining that the first confidence level does not exceed the first threshold confidence level, the digital assistant object can be displayed as remaining in the first state. For example, the digital assistant object can continue to be represented as a relatively small object (e.g., a small circular object with a corresponding animation and / or color set) to indicate to the user that the digital assistant is waiting for voice input, but that speech directed to the digital assistant has not yet been recognized. In this case, a second plurality of values ​​908 associated with a predetermined duration 910 is determined. The second plurality of values ​​908 can correspond to a predetermined duration 910 of the second voice input 912, such as two seconds of speech. Therefore, based on the first plurality of values ​​906 and the second plurality of values ​​908, a second confidence level corresponding to the second voice input 912 is determined at determination step 914. Based on determining that the second confidence level exceeds the second threshold confidence level at determination step 914, the digital assistant object is displayed in the second state and continues to receive the second voice input 912 (e.g., as described with respect to Figure 8 812). Additional variables may also be considered during determination step 914. For example, the duration between response 904 (e.g., the beginning of response 904, the middle of response 904, the end of response 904) and the beginning of second speech input 912 may affect the outcome of determination step 914. Specifically, a shorter duration between response 904 and second speech input 912 may result in an adjustment, such as an increase, to the second confidence level.

[0261] The context associated with the displayed information may also affect the various confidence level adjustments. For example, a user may be viewing a map application that includes various displayed affordances such as roads and points of interest (e.g., restaurants, stores, etc.). The contextual information associated with affordances may include location information related to the points of interest, route information, various voice-related keywords that may be related to the displayed information (e.g., "go," "map," "route," etc.), etc. The contextual information may further indicate whether the user's gaze is directed at the various affordances (e.g., the user may see a specific point of interest on the map). Based on determining that the subsequent voice input is associated with the contextual information, a second confidence level is increased. For example, a user may say "route to here" when seeing a restaurant affordance depicted on the displayed map. If the use of the term "route" matches relevant keywords included in the contextual information, and / or matches the user's gaze directed at a affordance, it is determined that the voice input is associated with the contextual information. Therefore, the corresponding confidence level is based on the high likelihood of the user's voice "route to here" being directed at the digital assistant.

[0262] The contextual information may further include semantic representations of various concepts specific to the displayed information. For example, a user may be viewing a messaging application (e.g., instant messaging, email, etc.). Messaging applications may generally be associated with a particular region of semantic space that corresponds to words, phrases, and other terms related to messages (e.g., as opposed to different regions of semantic space corresponding to sports, dining, etc.). In response to receiving voice input, a semantic representation of the input may be obtained. For example, a user may say "respond to this message." A semantic representation corresponding to "message" may be identified based at least in part on the use of the words "respond" and "message." Based on determining that the semantic representation of the messaging application corresponds to the semantic representation of the voice input, a corresponding confidence level associated with the voice input is increased.

[0263] Typically, the state of a digital assistant can change based on display size, animation profile, color scheme, etc. Figure 10 , the first digital assistant state may correspond to a digital assistant object, such as digital assistant object 1002, having a first size. For example, once the digital assistant enters the first state and begins listening for user speech directed to the digital assistant (e.g., subsequent speech related to the initial interaction), digital assistant object 1002 is displayed. Digital assistant object 1002 may include various objects that move at a first speed. Once the digital assistant transitions to the second state, the digital assistant objects may be displayed as shown via digital assistant object 1004. Specifically, digital assistant object 1004 may be larger than digital assistant object 1002, the size of digital assistant object 1004 may fluctuate based on the amplitude of the received speech, and the various objects within digital assistant object 1004 may move at a faster speed relative to the objects within digital assistant object 1002. The animation or color scheme of digital assistant object 1004 may also be dynamically modified based on the amplitude of the received speech.

[0264] Once the digital assistant determines that a complete user utterance has been detected (e.g., based on endpoint detection), the digital assistant may transition to a third state, such as the state represented by digital assistant object 1006. The third state may correspond to a processing state. During the processing state, digital assistant object 1006 may be reduced in size relative to digital assistant object 1004 and may include various objects rotating at corresponding speeds. Here, during other states, the objects may be significantly different (e.g., smaller and / or colorless) from the objects within the digital assistant object. Once the digital assistant has completed processing the user's voice, the digital assistant may transition to a fourth state, such as the state represented by digital assistant object 1008. During the fourth state, digital assistant object 1008 may be displayed at a size consistent with digital assistant objects 1002 and 1006. In addition, digital assistant object 1008 may include a specific animation profile and a specific color scheme (e.g., a denser collection of rotating objects than depicted in digital assistant object 1002). Digital assistant object 1008 may represent the digital assistant, and the digital assistant provides a response (e.g., a sound and / or display response) based on the user's voice input. Once the digital assistant finishes providing a response, the digital assistant can return to the first state, as depicted by digital assistant object 1002.

[0265] In some examples, various sound outputs may indicate transitions between digital assistant states. Figure 9 , the user can interact with the digital assistant using a device such as a home speaker or wireless headphones connected to a smartphone. Once the first plurality of values ​​906 are obtained, the digital assistant can enter a first state. Here, in order to signal the digital assistant to enter the first state, a first corresponding sound output (e.g., a soft prompt tone, a ringtone, or a similar tone) is provided. When the digital assistant is in the first state, continuous ambient audio can also be provided. In some examples, when the digital assistant is invoked while additional audio is playing (e.g., when the user is listening to a song), the volume of the additional audio is reduced during the duration of the first state.

[0266] Additionally, based on determining at step 912 that the second confidence level exceeds the second threshold confidence level, the digital assistant enters the second state. Entry into the second state may be signaled by a second corresponding sound output that is different from the first corresponding sound output (e.g., a beep, ringtone, or similar tone that is louder or softer than the first output, two or more corresponding beeps, ringtones, etc.). Continuous ambient audio may also be provided while the digital assistant is in the second state, which may be significantly different from any continuous ambient audio provided during the first state. Alternatively, continuous ambient audio may be provided only in one or more states (e.g., the second state) and not in other states (e.g., the first state). In some examples, if the user is listening to media during the transition from the first state to the second state, the media volume may be further adjusted (e.g., lowered or slightly increased) upon transition to the second state. For example, when the digital assistant transitions to the first state, the media volume may initially be reduced to a first level, and the media volume may be further reduced upon transition to the second state. Various additional states, such as corresponding Figure 10 Those states of the digital assistant objects 1006 and 1008 in the example can be associated with corresponding audio outputs that are distinct from other states. Various state-specific audio outputs can be provided in conjunction with various digital assistant display states. For example, while the digital assistant objects transitioning between various states can also be displayed on a smartphone wirelessly connected to headphones, the user can hear the digital assistant transitioning between states through the wireless headphones.

[0267] Figures 11A to 11B A process 1100 for facilitating a continuous conversation with a digital assistant according to various examples is shown. For example, process 1100 is performed using one or more electronic devices that implement a digital assistant. In some examples, process 1100 is performed using a client-server system (e.g., system 100), and the blocks of process 1100 are divided in any manner between a server (e.g., DA server 106) and a client device. In other examples, the blocks of process 1100 are divided between a server and multiple client devices (e.g., a mobile phone and a smartwatch). Therefore, although portions of process 1100 are described herein as being performed by specific devices of a client-server system, it should be understood that process 1100 is not limited thereto. In other examples, process 1100 is performed using only a client device (e.g., user device 104) or only multiple client devices. In process 1100, some blocks are optionally combined, the order of some blocks is optionally changed, and some blocks are optionally omitted. In some examples, additional steps may be performed in conjunction with process 1100.

[0268] refer to Figure 11AAt box 1102, a first voice input is received from a user. At box 1104, in response to receiving the first voice input, a response based on the first voice input is provided. At box 1106, a first output corresponding to the digital assistant in the first state is provided. In some examples, providing the first output corresponding to the digital assistant in the first state includes at least one of displaying a digital assistant object in the first state and providing a sound output. At box 1108, a second voice input is received from the user. At box 1110, a first plurality of values ​​is obtained. In some examples, obtaining the first plurality of values ​​includes detecting a user gaze directed at a display of the electronic device, determining whether the user gaze is directed at the displayed digital assistant object, and obtaining corresponding values ​​of the first plurality of values ​​based on determining whether the user gaze is directed at the displayed digital assistant object. In some examples, obtaining the first plurality of values ​​includes detecting lip movements associated with the user, determining whether the lip movements correspond to the first voice input, and obtaining corresponding values ​​of the first plurality of values ​​based on the determination. In some examples, obtaining the first plurality of values ​​includes detecting a direction associated with the user gaze, and obtaining corresponding values ​​of the first plurality of values ​​based on the determined direction. In some examples, obtaining the first plurality of values ​​includes detecting location information associated with the electronic device, and obtaining corresponding values ​​in the first plurality of values ​​based on the location information. In some examples, obtaining the first plurality of values ​​includes determining whether speech is detected at the electronic device, and obtaining corresponding values ​​in the first plurality of values ​​based on determining that speech is detected at the electronic device. By utilizing various values ​​associated with the device and the user, the system takes advantage of unique information to determine whether the user's speech is directed to the digital assistant. Using this unique information improves the accuracy of speech recognition, thereby making the device more efficient. Therefore, these features reduce power usage and extend the battery life of the device by enabling the user to use the device more quickly and efficiently.

[0269] At block 1112, a first confidence level corresponding to the second voice input is obtained based on the first plurality of values. In some examples, based on determining that the second voice input is associated with a minimum threshold duration, a determination is made for each value in the first plurality of values ​​as to whether the corresponding value satisfies at least one rule. In some examples, based on determining that the corresponding value satisfies the at least one rule, the first confidence level is increased. In some examples, based on determining that the electronic device is configured for echo cancellation, obtaining the first plurality of values ​​is initiated in response to detecting the end of the first voice input. In some examples, based on determining that the electronic device is not configured for echo cancellation, obtaining the first plurality of values ​​is initiated in response to detecting the end of the provided response. By considering echo cancellation capabilities and the minimum threshold duration of speech, the system further optimizes the collection of values ​​and the determination of confidence by focusing analysis on the most relevant speech. This focus improves speech recognition accuracy, thereby improving the user experience. Thus, these features enable users to more effectively use their devices by eliminating irrelevant or incorrect responses and further providing users with the opportunity to rephrase, adjust, or otherwise modify their initial query.

[0270] refer to Figure 11B , at box 1114, it is determined whether the first confidence level exceeds a first threshold confidence level. In some examples, based on determining that the first confidence level exceeds the first threshold confidence level, a second plurality of values ​​is obtained, and a second confidence level corresponding to the second voice input is obtained based on the first plurality of values ​​and the second plurality of values. In some examples, based on determining that the second confidence level exceeds the second threshold confidence level, the second voice input continues to be received. In some examples, based on determining that the second confidence level does not exceed the second threshold confidence level, the second voice input is stopped from being received. By selectively receiving speech based on confidence levels derived from the corresponding values, the system better focuses on relevant speech that may be directed to the digital assistant. Focusing on relevant speech makes the device more efficient by saving system resources when irrelevant speech is detected. Therefore, these features reduce power usage and extend the battery life of the device by enabling the user to use the device more quickly and efficiently.

[0271] At block 1116, based on determining that the first confidence level exceeds a first threshold confidence level, a second output corresponding to the digital assistant in the second state is provided. At block 1118, the second voice input continues to be received. At block 1120, the digital assistant is maintained in the first state. In some examples, providing the first output corresponding to the digital assistant in the first state includes displaying a digital assistant object in the first state, wherein based on determining that the first confidence level does not exceed the first threshold confidence level, the digital assistant object remains displayed in the first state. At block 1122, a second plurality of values ​​associated with a predetermined duration of the second voice input is obtained. In some examples, obtaining the second plurality of values ​​includes identifying a user intent associated with the predetermined duration of the second voice input, determining whether the second voice input is directed to the digital assistant based on the user intent, and obtaining corresponding values ​​from the second plurality of values ​​based on the determination of whether the second voice input is directed to the digital assistant. In some examples, obtaining the second plurality of values ​​includes retrieving a first speaker profile associated with the first voice input, obtaining a second speaker profile associated with the second voice input, comparing the first speaker profile to the second speaker profile, and obtaining corresponding values ​​from the second plurality of values ​​based on the comparison. In some examples, obtaining a second plurality of values ​​includes obtaining a lattice embedding based on the speech recognition output, determining the user intent based on the lattice embedding, and obtaining corresponding values ​​in the second plurality of values ​​based on the user intent. In some examples, obtaining the second plurality of values ​​includes recognizing result candidates based on the second speech input. In some examples, in response to the recognition result candidates, an updated first plurality of values ​​and an updated second plurality of values ​​are obtained. In some examples, based on the updated first plurality of values ​​and the updated second plurality of values, an updated second confidence level corresponding to the second speech input is obtained. By utilizing various additional values ​​that may be associated with higher processing requirements, the system utilizes this selection information to provide enhanced user intent determination when necessary. This enhanced speech recognition makes the device more efficient by reducing the likelihood of incorrect speech interpretation. Therefore, these features reduce power usage and extend the battery life of the device by enabling the user to use the device more quickly and efficiently.

[0272] At box 1124, a second confidence level corresponding to the second voice input is obtained based on the first plurality of values ​​and the second plurality of values. In some examples, based on determining that the second confidence level exceeds a second threshold confidence level, the digital assistant object is displayed in a second state, and while the digital assistant object is displayed in the second state, the second voice input continues to be received. In some examples, an affordance is displayed, wherein the affordance is associated with contextual information. In some examples, based on determining that the second voice input is associated with the contextual information, the second confidence level is increased. In some examples, the contextual information includes a first semantic representation. In some examples, a second semantic representation associated with the second voice input is obtained, and based on determining that the first semantic representation corresponds to the second semantic representation, the second confidence level is increased. In some examples, the contextual information includes at least one predefined word. In some examples, at least one word included in the second voice input is recognized, and based on determining that the at least one predefined word corresponds to at least one recognized word, the second confidence level is increased. By considering factors such as contextual information and semantic representations, the system further enhances the determination of the intent of the received user speech. This enhanced speech recognition makes the device more effective by reducing the likelihood of incorrect speech interpretation. Thus, these features reduce power usage and extend the battery life of the device by enabling the user to use the device more quickly and efficiently.

[0273] The above reference Figures 11A to 11B The described operations are optionally performed by Figures 1 to 4 、 Figures 6A to 6B and 7A to 7C For example, the operations of process 1300 may be implemented by one or more of the following: operating system 718, application module 724, I / O processing module 728, STT processing module 730, natural language processing module 732, vocabulary index 744, task flow processing module 736, service processing module 738, media service 120-1, or processors 220, 410, and 704. A person skilled in the art will clearly know how to implement the process 1300 based on the above. Figures 1 to 4 、 Figures 6A to 6B and 7A to 7C The components depicted in the figure are used to implement other processes.

[0274] According to some specific implementations, a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium) is provided that stores 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.

[0275] According to some implementations, an electronic device (eg, a portable electronic device) is provided that includes means for performing any of the methods and processes described herein.

[0276] According to some implementations, an electronic device (eg, a portable electronic device) is provided that includes a processing unit configured to perform any of the methods and processes described herein.

[0277] According to some embodiments, an electronic device (e.g., a portable electronic device) is provided that includes one or more processors and a 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 and processes described herein.

[0278] For the purpose of explanation, the foregoing description is described with reference to specific embodiments. However, the above illustrative discussion is not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible based on the above teachings. These embodiments have been selected and described in order to best explain the principles of these techniques and their practical applications. Others skilled in the art will thus be able to best utilize these techniques and various embodiments with various modifications suitable for the specific purposes contemplated.

[0279] Although the present disclosure and examples have been fully described with reference to the accompanying drawings, it should be noted that various changes and modifications will become apparent to those skilled in the art. It should be understood that such changes and modifications are considered to be included within the scope of the present disclosure and examples defined by the claims.

[0280] As described above, one aspect of the present technology is to collect and use data that can be obtained from various sources to improve continuous conversations with digital assistants. The present disclosure contemplates that, in some instances, these collected data may include personal information data that uniquely identifies or can be used to contact or locate a specific person. Such personal information data may include demographic data, location-based data, phone numbers, email addresses, Twitter IDs, home addresses, data or records related to the user's health or fitness level (e.g., vital sign measurements, medication information, exercise information), date of birth, or any other identifying or personal information. However, this data is also not required to implement the above features and may be used in limited circumstances or may not be used at all.

[0281] This disclosure recognizes that the use of such personal information data within the present technology can be used to benefit users. For example, personal information such as eye gaze data can be used to determine whether a user is looking at a digital assistant object. Furthermore, this disclosure contemplates other uses of personal information data that can benefit users. For example, health and fitness data can be used to provide insights into a user's overall health or as positive feedback to individuals using technology to pursue health goals.

[0282] This disclosure contemplates that entities responsible for collecting, analyzing, disclosing, transmitting, storing, or otherwise using such personal information will adhere to established privacy policies and / or practices. Specifically, such entities should implement and adhere to privacy policies and practices that are recognized as meeting or exceeding industry or government requirements for maintaining the privacy and security of personal information. Such policies should be easily accessible to users and updated as the collection and / or use of data changes. Personal information collected from users should be used for the entity's legitimate and reasonable purposes and not shared or sold beyond those legitimate uses. Furthermore, such collection / sharing should be conducted with the user's informed consent. Furthermore, such entities should consider taking any necessary steps to safeguard and secure access to such personal information and ensure that others with access to the personal information adhere to their privacy policies and procedures. Furthermore, such entities may subject themselves to third-party assessments to demonstrate compliance with widely accepted privacy policies and practices. Furthermore, policies and practices should be tailored to the specific type of personal information collected and / or accessed and to applicable laws and standards, including jurisdictional considerations. For example, in the United States, the collection or access of 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. Therefore, different privacy practices should be maintained for different types of personal data in each country.

[0283] Regardless of the foregoing, the present disclosure also contemplates implementation scenarios in which users selectively block the use or access of personal information data. That is, the present disclosure contemplates providing hardware elements and / or software elements to prevent or block access to such personal information data. For example, the technology of the present invention can be configured to allow users to "opt in" or "opt out" of participating in the collection of personal information data at any time, anywhere, during or after registration for a service. In another example, a user may choose not to provide lip movement data. In yet another example, a user may choose to limit the details provided about eye gaze data. In addition to providing "opt-in" and "opt-out" options, the present disclosure contemplates providing notifications related to access or use of personal information. For example, a user may be notified that their personal information data will be accessed when downloading an application, and then reminded again just before the personal information data is accessed by the application.

[0284] Furthermore, it is an object of the present disclosure that personal information data should be managed and processed to minimize the risk of unintentional or unauthorized access or use. Risk can be minimized by limiting data collection 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 the privacy of users. Where appropriate, de-identification can be facilitated by removing specific identifiers (e.g., date of birth, etc.), controlling the amount or characteristics of stored data (e.g., collecting location data at a city level rather than an address level), controlling how data is stored (e.g., aggregating data across users), and / or other methods.

[0285] Thus, while the present disclosure broadly covers the use of personal information data to implement one or more of the various disclosed embodiments, the present disclosure also contemplates that various embodiments may be implemented without access to such personal information data. That is, various embodiments of the present technology will not be unable to function properly due to the lack of all or part of such personal information data. For example, a continuous conversation may be facilitated by inferring preferences based on non-personal information data or a minimal amount of personal information (such as anonymous eye gaze data, other non-personal information available to the continuous conversation system, or publicly available information).

Claims

1. A computer-implemented method comprising: At an electronic device having a memory and one or more processors: receiving a first voice input from a user; In response to receiving the first voice input, providing a response based on the first voice input; providing a first output corresponding to the digital assistant in a first state, wherein providing the first output comprises displaying a digital assistant object in the first state; receiving a second voice input from the user; Get the first multiple values; obtaining a first confidence level corresponding to the second speech input based on the first plurality of values; Based on determining that the first confidence level exceeds a first threshold confidence level: providing a second output corresponding to the digital assistant being in a second state; as well as Continue to receive the second voice input; as well as Based on determining that the first confidence level does not exceed the first threshold confidence level: maintaining display of the digital assistant object in the first state; obtaining a second plurality of values ​​associated with a predetermined duration of the second speech input; as well as A second confidence level corresponding to the second speech input is obtained based on the first plurality of values ​​and the second plurality of values.

2. The method according to claim 1, comprising: The electronic device is configured for echo cancellation according to: initiating obtaining the first plurality of values ​​in response to detecting an end of the first speech input; as well as Based on determining that the electronic device is not configured for echo cancellation: Obtaining the first plurality of values ​​is initiated in response to detecting an end of the provided response.

3. The method according to any one of claims 1 to 2, comprising: According to determining that the second speech input is associated with a minimum threshold duration: for each value in the first plurality of values, determining whether the corresponding value satisfies at least one rule; and The first confidence level is increased based on determining that the corresponding value satisfies at least one rule.

4. The method of any one of claims 1 to 2, wherein obtaining the first plurality of values ​​comprises: detecting a user gaze directed at a display of the electronic device; determining whether the user gaze is directed toward a displayed digital assistant object; as well as Based on the determination of whether the user's gaze is directed toward the displayed digital assistant object, a corresponding value from the first plurality of values ​​is obtained.

5. The method of any one of claims 1 to 2, wherein obtaining the first plurality of values ​​comprises: detecting lip movements associated with the user; determining whether the lip movement corresponds to the first speech input; as well as A corresponding value of the first plurality of values ​​is obtained based on the determining.

6. The method of any one of claims 1 to 2, wherein obtaining the first plurality of values ​​comprises: detecting the direction associated with the user's gaze; as well as A corresponding value of the first plurality of values ​​is obtained based on the determined direction.

7. The method of any one of claims 1 to 2, wherein obtaining a first plurality of values ​​comprises: detecting location information associated with the electronic device; as well as A corresponding value of the first plurality of values ​​is obtained based on the position information.

8. The method of any one of claims 1 to 2, wherein obtaining a first plurality of values ​​comprises: determining whether speech is detected at the electronic device; as well as Based on determining that speech is detected at the electronic device, a corresponding value of the first plurality of values ​​is obtained.

9. The method according to any one of claims 1 to 2, comprising: Based on determining that the first confidence level exceeds a first threshold confidence level: Get the second multiple values; obtaining a second confidence level corresponding to the second speech input based on the first plurality of values ​​and the second plurality of values; Determining that the second confidence level exceeds a second threshold confidence level based on: Continue to receive the second voice input; and Determining that the second confidence level does not exceed a second threshold confidence level is based on: Stop receiving the second voice input.

10. The method of claim 9, wherein obtaining the second plurality of values ​​comprises: identifying a user intent associated with a predetermined duration of the second voice input; determining whether the second voice input is directed to a digital assistant based on the user intent; as well as A corresponding value from the second plurality of values ​​is obtained based on the determination of whether the second voice input is directed to a digital assistant.

11. The method of claim 9, wherein obtaining the second plurality of values ​​comprises: retrieving a first speaker profile associated with the first speech input; obtaining a second speaker profile associated with the second speech input; comparing the first speaker profile to the second speaker profile; as well as A corresponding value in the second plurality of values ​​is obtained based on the comparison.

12. The method of claim 9, wherein obtaining a second plurality of values ​​comprises: Obtaining lattice embedding based on speech recognition output; determining user intent based on the lattice embedding; as well as A corresponding value of the second plurality of values ​​is obtained based on the user intent.

13. The method of claim 9, wherein obtaining a second plurality of values ​​comprises: Recognize candidate results based on the second voice input; as well as In response to identifying the result candidate: obtaining an updated first plurality of values ​​and an updated second plurality of values; as well as An updated second confidence level corresponding to the second speech input is obtained based on the updated first plurality of values ​​and the updated second plurality of values.

14. The method according to claim 1, comprising: Determining that the second confidence level exceeds a second threshold confidence level based on: displaying the digital assistant object in a second state; as well as While the digital assistant object in the second state is displayed, the second voice input continues to be received.

15. The method according to claim 1, comprising: displaying an affordance, wherein the affordance is associated with contextual information; as well as Based on determining that the second speech input is associated with the contextual information, the second confidence level is increased.

16. The method according to claim 15, wherein the context information comprises a first semantic representation, the method comprising: Obtaining a second semantic representation associated with the second speech input; as well as Based on determining that the first semantic representation corresponds to the second semantic representation, the second confidence level is increased.

17. The method according to claim 15, wherein the context information includes at least one predefined word, the method comprising: identifying at least one word included in the second speech input; as well as The second confidence level is increased based on determining that the at least one predefined word corresponds to the recognized at least one word.

18. The method of any one of claims 1 to 2, wherein providing a first output corresponding to the digital assistant in the first state comprises at least one of: displaying a digital assistant object in the first state, and providing a sound output.

19. A computer-readable storage medium storing one or more programs, the one or more programs comprising instructions that, when executed by one or more processors of a first electronic device, cause the first electronic device to perform the following operations: receiving a first voice input from a user; In response to receiving the first voice input, providing a response based on the first voice input; providing a first output corresponding to the digital assistant in a first state, wherein providing the first output comprises displaying a digital assistant object in the first state; receiving a second voice input from the user; Get the first multiple values; obtaining a first confidence level corresponding to the second speech input based on the first plurality of values; Based on determining that the first confidence level exceeds a first threshold confidence level: providing a second output corresponding to the digital assistant being in a second state; as well as Continue to receive the second voice input; as well as Based on determining that the first confidence level does not exceed the first threshold confidence level: maintaining display of the digital assistant object in the first state; obtaining a second plurality of values ​​associated with a predetermined duration of the second speech input; as well as A second confidence level corresponding to the second speech input is obtained based on the first plurality of values ​​and the second plurality of values.

20. The computer-readable storage medium of claim 19, wherein: The instructions cause the first electronic device to perform the following operations: The electronic device is configured for echo cancellation according to: initiating obtaining the first plurality of values ​​in response to detecting an end of the first speech input; and Based on determining that the electronic device is not configured for echo cancellation: Obtaining the first plurality of values ​​is initiated in response to detecting an end of the provided response.

21. The computer-readable storage medium according to any one of claims 19 to 20, wherein: The instructions cause the first electronic device to perform the following operations: According to determining that the second speech input is associated with a minimum threshold duration: for each value in the first plurality of values, determining whether the corresponding value satisfies at least one rule; and The first confidence level is increased based on determining that the corresponding value satisfies at least one rule.

22. The computer-readable storage medium of any one of claims 19 to 20, wherein obtaining the first plurality of values ​​comprises: detecting a user gaze directed at a display of the electronic device; determining whether the user gaze is directed toward a displayed digital assistant object; as well as Based on the determination of whether the user's gaze is directed toward the displayed digital assistant object, a corresponding value from the first plurality of values ​​is obtained.

23. The computer-readable storage medium of any one of claims 19 to 20, wherein obtaining the first plurality of values ​​comprises: detecting lip movements associated with the user; determining whether the lip movement corresponds to the first speech input; as well as A corresponding value of the first plurality of values ​​is obtained based on the determining.

24. The computer-readable storage medium of any one of claims 19 to 20, wherein obtaining the first plurality of values ​​comprises: detecting the direction associated with the user's gaze; as well as A corresponding value of the first plurality of values ​​is obtained based on the determined direction.

25. The computer-readable storage medium of any one of claims 19 to 20, wherein obtaining the first plurality of values ​​comprises: detecting location information associated with the electronic device; as well as A corresponding value of the first plurality of values ​​is obtained based on the position information.

26. The computer-readable storage medium of any one of claims 19 to 20, wherein obtaining the first plurality of values ​​comprises: determining whether speech is detected at the electronic device; as well as Based on determining that speech is detected at the electronic device, a corresponding value of the first plurality of values ​​is obtained.

27. The computer-readable storage medium according to any one of claims 19 to 20, wherein: The instructions cause the first electronic device to perform the following operations: Based on determining that the first confidence level exceeds a first threshold confidence level: Get the second multiple values; obtaining a second confidence level corresponding to the second speech input based on the first plurality of values ​​and the second plurality of values; Determining that the second confidence level exceeds a second threshold confidence level based on: Continue to receive the second voice input; and Determining that the second confidence level does not exceed a second threshold confidence level is based on: Stop receiving the second voice input.

28. The computer-readable storage medium of claim 27, wherein obtaining the second plurality of values ​​comprises: identifying a user intent associated with a predetermined duration of the second voice input; determining whether the second voice input is directed to a digital assistant based on the user intent; as well as A corresponding value from the second plurality of values ​​is obtained based on the determination of whether the second voice input is directed to a digital assistant.

29. The computer-readable storage medium of claim 27, wherein obtaining the second plurality of values ​​comprises: retrieving a first speaker profile associated with the first speech input; obtaining a second speaker profile associated with the second speech input; comparing the first speaker profile to the second speaker profile; as well as A corresponding value in the second plurality of values ​​is obtained based on the comparison.

30. The computer-readable storage medium of claim 27, wherein obtaining the second plurality of values ​​comprises: Obtaining lattice embedding based on speech recognition output; determining user intent based on the lattice embedding; as well as A corresponding value of the second plurality of values ​​is obtained based on the user intent.

31. The computer-readable storage medium of claim 27, wherein obtaining the second plurality of values ​​comprises: Recognize candidate results based on the second voice input; as well as In response to identifying the result candidate: obtaining an updated first plurality of values ​​and an updated second plurality of values; as well as An updated second confidence level corresponding to the second speech input is obtained based on the updated first plurality of values ​​and the updated second plurality of values.

32. The computer-readable storage medium of claim 19, wherein: The instructions cause the first electronic device to perform the following operations: Determining that the second confidence level exceeds a second threshold confidence level based on: displaying the digital assistant object in a second state; and While the digital assistant object in the second state is displayed, the second voice input continues to be received.

33. The computer-readable storage medium of claim 19, wherein: The instructions cause the first electronic device to perform the following operations: displaying an affordance, wherein the affordance is associated with contextual information; and Based on determining that the second speech input is associated with the contextual information, the second confidence level is increased.

34. The computer-readable storage medium of claim 33, wherein the context information comprises a first semantic representation, wherein: The instructions cause the first electronic device to perform the following operations: Obtaining a second semantic representation associated with the second speech input; and Based on determining that the first semantic representation corresponds to the second semantic representation, the second confidence level is increased.

35. The computer-readable storage medium of claim 33, wherein the context information includes at least one predefined word, wherein The instructions cause the first electronic device to perform the following operations: identifying at least one word included in the second speech input; and The second confidence level is increased based on determining that the at least one predefined word corresponds to the recognized at least one word.

36. A computer-readable storage medium according to any one of claims 19 to 20, wherein providing a first output corresponding to the digital assistant in the first state includes at least one of: displaying a digital assistant object in the first state, and providing a sound output.

37. An electronic device comprising: one or more processors; Memory; and One or more programs, wherein 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: receiving a first voice input from a user; In response to receiving the first voice input, providing a response based on the first voice input; providing a first output corresponding to the digital assistant in a first state, wherein providing the first output comprises displaying a digital assistant object in the first state; receiving a second voice input from the user; Get the first multiple values; obtaining a first confidence level corresponding to the second speech input based on the first plurality of values; Based on determining that the first confidence level exceeds a first threshold confidence level: providing a second output corresponding to the digital assistant being in a second state; as well as Continue to receive the second voice input; as well as Based on determining that the first confidence level does not exceed the first threshold confidence level: maintaining display of the digital assistant object in the first state; obtaining a second plurality of values ​​associated with a predetermined duration of the second speech input; as well as A second confidence level corresponding to the second speech input is obtained based on the first plurality of values ​​and the second plurality of values.

38. The electronic device of claim 37, wherein the one or more programs include instructions for: The electronic device is configured for echo cancellation according to: initiating obtaining the first plurality of values ​​in response to detecting an end of the first speech input; and Based on determining that the electronic device is not configured for echo cancellation: Obtaining the first plurality of values ​​is initiated in response to detecting an end of the provided response.

39. The electronic device according to any one of claims 37 to 38, wherein the one or more programs include instructions for: According to determining that the second speech input is associated with a minimum threshold duration: for each value in the first plurality of values, determining whether the corresponding value satisfies at least one rule; and The first confidence level is increased based on determining that the corresponding value satisfies at least one rule.

40. The electronic device of any one of claims 37 to 38, wherein obtaining the first plurality of values ​​comprises: detecting a user gaze directed at a display of the electronic device; determining whether the user gaze is directed toward a displayed digital assistant object; as well as Based on the determination of whether the user's gaze is directed toward the displayed digital assistant object, a corresponding value from the first plurality of values ​​is obtained.

41. The electronic device of any one of claims 37 to 38, wherein obtaining the first plurality of values ​​comprises: detecting lip movements associated with the user; determining whether the lip movement corresponds to the first speech input; as well as A corresponding value of the first plurality of values ​​is obtained based on the determining.

42. The electronic device of any one of claims 37 to 38, wherein obtaining the first plurality of values ​​comprises: detecting the direction associated with the user's gaze; as well as A corresponding value of the first plurality of values ​​is obtained based on the determined direction.

43. The electronic device of any one of claims 37 to 38, wherein obtaining the first plurality of values ​​comprises: detecting location information associated with the electronic device; as well as A corresponding value of the first plurality of values ​​is obtained based on the position information.

44. The electronic device of any one of claims 37 to 38, wherein obtaining the first plurality of values ​​comprises: determining whether speech is detected at the electronic device; as well as Based on determining that speech is detected at the electronic device, a corresponding value of the first plurality of values ​​is obtained.

45. The electronic device of any one of claims 37 to 38, wherein the one or more programs include instructions for: Based on determining that the first confidence level exceeds a first threshold confidence level: Get the second multiple values; obtaining a second confidence level corresponding to the second speech input based on the first plurality of values ​​and the second plurality of values; Determining that the second confidence level exceeds a second threshold confidence level based on: Continue to receive the second voice input; and Determining that the second confidence level does not exceed a second threshold confidence level is based on: Stop receiving the second voice input.

46. ​​The electronic device of claim 45, wherein obtaining the second plurality of values ​​comprises: identifying a user intent associated with a predetermined duration of the second voice input; determining whether the second voice input is directed to a digital assistant based on the user intent; as well as A corresponding value from the second plurality of values ​​is obtained based on the determination of whether the second voice input is directed to a digital assistant.

47. The electronic device of claim 45, wherein obtaining the second plurality of values ​​comprises: retrieving a first speaker profile associated with the first speech input; obtaining a second speaker profile associated with the second speech input; comparing the first speaker profile to the second speaker profile; as well as A corresponding value in the second plurality of values ​​is obtained based on the comparison.

48. The electronic device of claim 45, wherein obtaining the second plurality of values ​​comprises: Obtaining lattice embedding based on speech recognition output; determining user intent based on the lattice embedding; as well as A corresponding value of the second plurality of values ​​is obtained based on the user intent.

49. The electronic device of claim 45, wherein obtaining the second plurality of values ​​comprises: Recognize candidate results based on the second voice input; as well as In response to identifying the result candidate: obtaining an updated first plurality of values ​​and an updated second plurality of values; as well as An updated second confidence level corresponding to the second speech input is obtained based on the updated first plurality of values ​​and the updated second plurality of values.

50. The electronic device of claim 37, wherein the one or more programs include instructions for: Determining that the second confidence level exceeds a second threshold confidence level based on: displaying the digital assistant object in a second state; and While the digital assistant object in the second state is displayed, the second voice input continues to be received.

51. The electronic device of claim 37, wherein the one or more programs include instructions for: displaying an affordance, wherein the affordance is associated with contextual information; and Based on determining that the second speech input is associated with the contextual information, the second confidence level is increased.

52. The electronic device of claim 51 , wherein the context information comprises a first semantic representation, and the one or more programs comprise instructions for: Obtaining a second semantic representation associated with the second speech input; and Based on determining that the first semantic representation corresponds to the second semantic representation, the second confidence level is increased.

53. The electronic device of claim 51 , wherein the context information comprises at least one predefined word, and the one or more programs comprise instructions for: identifying at least one word included in the second speech input; and The second confidence level is increased based on determining that the at least one predefined word corresponds to the recognized at least one word.

54. An electronic device according to any one of claims 37 to 38, wherein providing a first output corresponding to the digital assistant in the first state includes at least one of: displaying a digital assistant object in the first state, and providing a sound output.

55. An electronic device comprising: Device for carrying out the method according to any one of claims 1 to 18.

56. A computer program product comprising one or more programs configured to be executed by one or more processors of a computer system in communication with a display generating component and one or more input devices, the one or more programs including instructions for performing the method according to any one of claims 1 to 18.

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