An example method includes, at an electronic device: receiving an indication of a notification; in accordance with receiving the indication of the notification: obtaining one or more data streams from one or more sensors; determining, based on the one or more data streams, whether a user associated with the electronic device is speaking; and in accordance with a determination that the user is not speaking: causing an output associated with the notification to be provided.

A dialogue system includes a voice recognition module provided to execute voice recognition, a storage device in which a result of the executed voice recognition is stored, and a controller configured to determine priorities of an external event and the voice recognition when the external event occurs while an utterance of a user is input, and pause the execution of the voice recognition and store a result of the voice recognition of the utterance of the user inputted before the pause in the storage device, when the controller concludes that the priority of the external event is higher than the priority of the voice recognition.

Disclosed herein are systems and methods for receiving a voice command and determining an appropriate action for the media playback system to execute based on user identification. The systems and methods receive a voice command for a media playback system, and determines whether the voice command was received from a registered user of the media playback system. In response to determining that the voice command was received from a registered user, the systems and methods configure an instruction for the media playback system based on content from the voice command and information in a user profile for the registered user.

The presentation of an automated assistant response may be selectively pre-empted in response to a hot-word free utterance that is received during the presentation and that is determined to be likely directed to the automated assistant. The determination that the utterance is likely directed to the automated assistant may be performed, for example, using an utterance classification operation that is performed on audio data received during presentation of the response, and based upon such a determination, the response may be pre-empted with another response associated with the later-received utterance. In addition, the duration that is used to determine when a session should be terminated at the conclusion of a conversation between a user and an automated assistant may be dynamically controlled based upon when the presentation of a response has completed.

Systems and processes for operating an intelligent automated assistant are provided. For example, a first speech input is received from a user. In response to receiving the first speech input, a response is provided. A first output is provided corresponding to a digital assistant in a first state, and a second speech 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 speech input is obtained. In accordance with a determination that the first confidence level exceeds a first threshold confidence level, a second output is provided corresponding to the digital assistant in a second state. The second speech input continues to be received.

Conversational understanding systems allow users to conversationally interface with a computing device. In examples, a query may be received that includes a request for execution of a task. A data exchange task definition may be accessed. The data exchange task definition assists a conversational understanding system in managing task state tracking for information needed for task execution. Using the data exchange task definition, a per-turn policy for interacting with the user computing device is generated based on the state of a dialogue with a computing device and an evaluation of a process flow chart provided by a task owner resource. The task owner resource may be independent from the conversational understanding system. A response to the query may be generated and output based on the per-turn policy. In examples, the per-turn policy is used to generate one or more responses during a dialogue with a user via a computing device.

Systems and methods are described for handling interruptions during a digital assistant session between a user and a digital assistant by detecting if an interruption event is to occur during the digital assistant session. In response to detecting that the interruption event is to occur, an operation that addresses the interruption event may be caused to be performed.

An on-vehicle device includes: a plurality of agent function units configured to provide services including causing an output unit to output an audio response in response to an utterance of an occupant of a vehicle; and a content management unit configured to determine whether or not the instructed content is stored in an in-vehicle storage device mounted in the vehicle or a portable storage medium brought into the vehicle when the playback of the content is instructed by the utterance of the occupant, and to cause the playback device to play back the content present in the in-vehicle storage device or the portable storage medium when the instructed content is determined as being stored in the in-vehicle storage device or the portable storage medium.

The present disclosure provides a method for denoising voice data, an electronic device, and a computer readable storage medium. The present disclosure relates to the technical field of artificial intelligence, such as Internet of Vehicles, smart cockpit, smart voice, and voice recognition. A specific embodiment of the method includes: receiving an input to-be-played first piece of voice data; and invoking, in response to not detecting a synthetic voice interruption signal in a process of playing the first piece of voice data, a preset first denoising algorithm to filter out noise data except for the first piece of voice data.

In non-limiting examples of the present disclosure, systems, methods and devices for providing personalized experiences to a computing device based on user input such as voice, text and gesture input are provided. Acoustic patterns associated with voice input, speech patterns, language patterns and natural language processing may be used to identify a specific user providing input from a plurality of users, identify user background characteristics and traits for the specific user, and topically categorize user input in a tiered hierarchical index. Topically categorized user input may be supplemented with user data and world knowledge and personalized responses and feedback for an identified specific user may be provided reactively and proactively.