USING LARGE LANGUAGE MODEL(S) IN GENERATING AUTOMATED ASSISTANT RESPONSE(S

    公开(公告)号:US20230074406A1

    公开(公告)日:2023-03-09

    申请号:US17532794

    申请日:2021-11-22

    Applicant: GOOGLE LLC

    Abstract: As part of a dialog session between a user and an automated assistant, implementations can receive a stream of audio data that captures a spoken utterance including an assistant query, determine, based on processing the stream of audio data, a set of assistant outputs that are each predicted to be responsive to the assistant query, process, using large language model (LLM) output(s), the assistant outputs and context of the dialog session to generate a set of modified assistant outputs, and cause given modified assistant output, from among the set of modified assistant outputs, to be provided for presentation to the user in response to the spoken utterance. In some implementations, the LLM output(s) can be generated in an offline manner for subsequent use in an online manner. In additional or alternative implementations, the LLM output(s) can be generated in an online manner when the spoken utterance is received.

    DYNAMICALLY ADAPTING GIVEN ASSISTANT OUTPUT BASED ON A GIVEN PERSONA ASSIGNED TO AN AUTOMATED ASSISTANT

    公开(公告)号:US20230343323A1

    公开(公告)日:2023-10-26

    申请号:US17726244

    申请日:2022-04-21

    Applicant: GOOGLE LLC

    CPC classification number: G10L13/10 G10L15/22 G10L15/1815 G10L2015/223

    Abstract: Implementations relate to dynamically adapting a given assistant output based on a given persona, from among a plurality of disparate personas, assigned to an automated assistant. In some implementations, the given assistant output can be generated and subsequently adapted based on the given persona assigned to the automated assistant. In other implementations, the given assistant output can be generated specific to the given persona and without having to subsequently adapt the given assistant output to the given persona. Notably, the given assistant output can include a stream of textual content to be synthesized for audible presentation to the user, and a stream of visual cues utilized in controlling a display of a client device and/or in controlling a visualized representation of the automated assistant. Various implementations utilize large language models (LLMs), or output previously generated utilizing LLMs, to reflect the given persona in the given assistant output.

    USING LARGE LANGUAGE MODEL(S) IN GENERATING AUTOMATED ASSISTANT RESPONSE(S)

    公开(公告)号:US20250037711A1

    公开(公告)日:2025-01-30

    申请号:US18912175

    申请日:2024-10-10

    Applicant: GOOGLE LLC

    Abstract: As part of a dialog session between a user and an automated assistant, implementations can receive a stream of audio data that captures a spoken utterance including an assistant query, determine, based on processing the stream of audio data, a set of assistant outputs that are each predicted to be responsive to the assistant query, process, using large language model (LLM) output(s), the assistant outputs and context of the dialog session to generate a set of modified assistant outputs, and cause given modified assistant output, from among the set of modified assistant outputs, to be provided for presentation to the user in response to the spoken utterance. In some implementations, the LLM output(s) can be generated in an offline manner for subsequent use in an online manner. In additional or alternative implementations, the LLM output(s) can be generated in an online manner when the spoken utterance is received.

    Using large language model(s) in generating automated assistant response(s

    公开(公告)号:US12148421B2

    公开(公告)日:2024-11-19

    申请号:US17532794

    申请日:2021-11-22

    Applicant: GOOGLE LLC

    Abstract: As part of a dialog session between a user and an automated assistant, implementations can receive a stream of audio data that captures a spoken utterance including an assistant query, determine, based on processing the stream of audio data, a set of assistant outputs that are each predicted to be responsive to the assistant query, process, using large language model (LLM) output(s), the assistant outputs and context of the dialog session to generate a set of modified assistant outputs, and cause given modified assistant output, from among the set of modified assistant outputs, to be provided for presentation to the user in response to the spoken utterance. In some implementations, the LLM output(s) can be generated in an offline manner for subsequent use in an online manner. In additional or alternative implementations, the LLM output(s) can be generated in an online manner when the spoken utterance is received.

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