Transferring dialog data from an initially invoked automated assistant to a subsequently invoked automated assistant

    公开(公告)号:US12260858B2

    公开(公告)日:2025-03-25

    申请号:US17532276

    申请日:2021-11-22

    Applicant: GOOGLE LLC

    Abstract: Systems and methods for providing dialog data, from an initially invoked automated assistant to a subsequently invoked automated assistant. A first automated assistant may be invoked by a user utterance, followed by a dialog with the user that is processed by the first automated assistant. During the dialog, a request to transfer dialog data to a second automated assistant is received. The request may originate with the user, by the first automated assistant, and/or by the second automated assistant. Once authorized, the first automated assistant provides the previous dialog data to the second automated assistant. The second automated assistant performs one or more actions based on the dialog data.

    Foundational Models for Semantic Routing

    公开(公告)号:US20250093164A1

    公开(公告)日:2025-03-20

    申请号:US18468338

    申请日:2023-09-15

    Applicant: Google LLC

    Abstract: Training data is obtained. The training data includes (a) route information indicative of a route from a starting location to a destination location, wherein the route comprises a plurality of route segments comprising a first subset of route segments and a second subset of route segments, and (b) route characteristic information descriptive of one or more route characteristics. At least the first subset of route segments and a portion of the route characteristic information associated with the first subset of route segments is processed with a machine-learned semantic routing model to obtain one or more predicted route segments for the second subset of route segments. One or more parameters of the machine-learned semantic routing model are adjusted based on an optimization function that evaluates a difference between the one or more predicted route segments and the second subset of route segments.

    Detecting and handling failures in other assistants

    公开(公告)号:US12254885B2

    公开(公告)日:2025-03-18

    申请号:US18097157

    申请日:2023-01-13

    Applicant: GOOGLE LLC

    Abstract: Techniques are described herein for detecting and handling failures in other automated assistants. A method includes: executing a first automated assistant in an inactive state at least in part on a computing device operated by a user; while in the inactive state, determining, by the first automated assistant, that a second automated assistant failed to fulfill a request of the user; in response to determining that the second automated assistant failed to fulfill the request of the user, the first automated assistant processing cached audio data that captures a spoken utterance of the user comprising the request that the second automated assistant failed to fulfill, or features of the cached audio data, to determine a response that fulfills the request of the user; and providing, by the first automated assistant to the user, the response that fulfills the request of the user.

    ADAPTIVE SENDING OR RENDERING OF AUDIO WITH TEXT MESSAGES SENT VIA AUTOMATED ASSISTANT

    公开(公告)号:US20250054495A1

    公开(公告)日:2025-02-13

    申请号:US18446798

    申请日:2023-08-09

    Applicant: GOOGLE LLC

    Abstract: Implementations set forth herein relate to an automated assistant that can selectively communicate audio data to a recipient when a user solicits the automated assistant to send a text message to the recipient. The audio data can include a snippet of audio that characterizes content of the text message, and the automated assistant can communicate the audio data to the recipient when score data for a speech recognition hypothesis does not satisfy a confidence threshold. The score data can correspond to an entirety of content of a text message and/or speech recognition hypothesis, and/or less than an entirety of the content. A recipient device can optionally re-process the audio data using a model that is associated with the recipient device. This can provide more accurate transcripts in some instances, thereby improving accuracy of communications and decreasing a number of corrective messages sent between users.

    Lane selection using machine learning

    公开(公告)号:US12223410B2

    公开(公告)日:2025-02-11

    申请号:US18589391

    申请日:2024-02-27

    Applicant: GOOGLE LLC

    Abstract: To select a lane in a multi-lane road segment for a vehicle travelling on the road segment, a system identifies, in multiple lanes and in a region ahead of the vehicle, another vehicle defining a target; the system applies an optical flow technique to track the target during a period of time, to generate an estimate of how fast traffic moves; and the system applies the estimate to machine learning (ML) model to generate a recommendation which one of the plurality of lanes the vehicle is to choose.

    VOICE-BASED SCENE SELECTION FOR VIDEO CONTENT ON A COMPUTING DEVICE

    公开(公告)号:US20250047930A1

    公开(公告)日:2025-02-06

    申请号:US18923464

    申请日:2024-10-22

    Applicant: GOOGLE LLC

    Abstract: Voice-based interaction with video content being presented by a media player application is enhanced through the use of an automated assistant capable of identifying when a spoken utterance by a user is a request to playback a specific scene in the video content. A query identified in a spoken utterance may be used to access stored scene metadata associated with video content being presented in the vicinity of the user to identify one or more locations in the video content that correspond to the query, such that a media control command may be issued to the media player application to cause the media player application to seek to a particular location in the video content that satisfies the query.

    HANDLING CONTRADICTORY QUERIERS ON A SHARED DEVICE

    公开(公告)号:US20250045326A1

    公开(公告)日:2025-02-06

    申请号:US18919620

    申请日:2024-10-18

    Applicant: Google LLC

    Abstract: A method for handling contradictory queries on a shared device includes receiving a first query issued by a first user, the first query specifying a first long-standing operation for a digital assistant to perform, and while the digital assistant is performing the first long-standing operation, receiving a second query, the second query specifying a second long-standing operation for the digital assistant to perform. The method also includes determining that the second query was issued by another user different than the first user and determining, using a query resolver, that performing the second long-standing operation would conflict with the first long-standing operation. The method further includes identifying one or more compromise operations for the digital assistant to perform, and instructing the digital assistant to perform a selected compromise operation among the identified one or more compromise operations.

    Digital signal processor-based continued conversation

    公开(公告)号:US12217751B2

    公开(公告)日:2025-02-04

    申请号:US17644394

    申请日:2021-12-15

    Applicant: Google LLC

    Abstract: A method includes instructing an always-on first processor to operate in a follow-on query detection mode, and while the always-on first processor operates in the follow-on query detection mode: receiving follow-on audio data captured by the assistant-enabled device; determining, using a voice activity detection (VAD) model executing on the always-on first processor, whether or not the VAD model detects voice activity in the follow-on audio data; performing, using a speaker identification (SID) model executing on the always-on first processor, speaker verification on the follow-on audio data to determine whether the follow-on audio data includes an utterance spoken by the same user. The method also includes initiating a wake-up process on a second processor to determine whether the utterance includes a follow-on query.

    Simultaneous acoustic event detection across multiple assistant devices

    公开(公告)号:US12217736B2

    公开(公告)日:2025-02-04

    申请号:US18367859

    申请日:2023-09-13

    Applicant: GOOGLE LLC

    Abstract: Implementations can detect respective audio data that captures an acoustic event at multiple assistant devices in an ecosystem that includes a plurality of assistant devices, process the respective audio data locally at each of the multiple assistant devices to generate respective measures that are associated with the acoustic event using respective event detection models, process the respective measures to determine whether the detected acoustic event is an actual acoustic event, and cause an action associated with the actional acoustic event to be performed in response to determining that the detected acoustic event is the actual acoustic event. In some implementations, the multiple assistant devices that detected the respective audio data are anticipated to detect the respective audio data that captures the actual acoustic event based on a plurality of historical acoustic events being detected at each of the multiple assistant devices.

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