SUPPLEMENTING VOICE INPUTS TO AN AUTOMATED ASSISTANT ACCORDING TO SELECTED SUGGESTIONS

    公开(公告)号:US20240420696A1

    公开(公告)日:2024-12-19

    申请号:US18814060

    申请日:2024-08-23

    Applicant: GOOGLE LLC

    Abstract: Implementations described herein relate to providing suggestions, via a display modality, for completing a spoken utterance for an automated assistant, in order to reduce a frequency and/or a length of time that the user will participate in a current and/or subsequent dialog session with the automated assistant. A user request can be compiled from content of an ongoing spoken utterance and content of any selected suggestion elements. When a currently compiled portion of the user request (from content of a selected suggestion(s) and an incomplete spoken utterance) is capable of being performed via the automated assistant, any actions corresponding to the currently compiled portion of the user request can be performed via the automated assistant. Furthermore, any further content resulting from performance of the actions, along with any discernible context, can be used for providing further suggestions.

    Acoustic model training using corrected terms

    公开(公告)号:US11682381B2

    公开(公告)日:2023-06-20

    申请号:US17457421

    申请日:2021-12-02

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for speech recognition. One of the methods includes receiving first audio data corresponding to an utterance; obtaining a first transcription of the first audio data; receiving data indicating (i) a selection of one or more terms of the first transcription and (ii) one or more of replacement terms; determining that one or more of the replacement terms are classified as a correction of one or more of the selected terms; in response to determining that the one or more of the replacement terms are classified as a correction of the one or more of the selected terms, obtaining a first portion of the first audio data that corresponds to one or more terms of the first transcription; and using the first portion of the first audio data that is associated with the one or more terms of the first transcription to train an acoustic model for recognizing the one or more of the replacement terms.

    ACOUSTIC MODEL TRAINING USING CORRECTED TERMS

    公开(公告)号:US20230274729A1

    公开(公告)日:2023-08-31

    申请号:US18312587

    申请日:2023-05-04

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for speech recognition. One of the methods includes receiving first audio data corresponding to an utterance; obtaining a first transcription of the first audio data; receiving data indicating (i) a selection of one or more terms of the first transcription and (ii) one or more of replacement terms; determining that one or more of the replacement terms are classified as a correction of one or more of the selected terms; in response to determining that the one or more of the replacement terms are classified as a correction of the one or more of the selected terms, obtaining a first portion of the first audio data that corresponds to one or more terms of the first transcription; and using the first portion of the first audio data that is associated with the one or more terms of the first transcription to train an acoustic model for recognizing the one or more of the replacement terms.

    SUPPLEMENTING VOICE INPUTS TO AN AUTOMATED ASSISTANT ACCORDING TO SELECTED SUGGESTIONS

    公开(公告)号:US20210280180A1

    公开(公告)日:2021-09-09

    申请号:US16343683

    申请日:2019-02-07

    Applicant: Google LLC

    Abstract: Implementations described herein relate to providing suggestions, via a display modality, for completing a spoken utterance for an automated assistant, in order to reduce a frequency and/or a length of time that the user will participate in a current and/or subsequent dialog session with the automated assistant. A user request can be compiled from content of an ongoing spoken utterance and content of any selected suggestion elements. When a currently compiled portion of the user request (from content of a selected suggestion(s) and an incomplete spoken utterance) is capable of being performed via the automated assistant, any actions corresponding to the currently compiled portion of the user request can be performed via the automated assistant. Furthermore, any further content resulting from performance of the actions, along with any discernible context, can be used for providing further suggestions.

    INTERACTIVE APPLICATION WIDGETS RENDERED WITH ASSISTANT CONTENT

    公开(公告)号:US20240061694A1

    公开(公告)日:2024-02-22

    申请号:US18235699

    申请日:2023-08-18

    Applicant: GOOGLE LLC

    CPC classification number: G06F9/453 G06F3/0482 G06F3/0484

    Abstract: Implementations set forth herein relate to an automated assistant that can provide interactive application widgets based on their relevance to content that a user may have expressed interest in. The automated assistant can render the application widgets according to an estimated familiarity of the user with the content they expressed interest in. Each application widget can correspond to an application that can be accessed separately from the automated assistant. An application widget can be rendered at a display interface simultaneous to the user accessing the content that served as the basis for rendering the application widget. When the user interacts with the application widget, the automated assistant can communicate selection data to a corresponding application, which can respond with supplemental data that can be rendered at the display interface.

    Supplementing voice inputs to an automated assistant according to selected suggestions

    公开(公告)号:US11238857B2

    公开(公告)日:2022-02-01

    申请号:US16343683

    申请日:2019-02-07

    Applicant: Google LLC

    Abstract: Implementations described herein relate to providing suggestions, via a display modality, for completing a spoken utterance for an automated assistant, in order to reduce a frequency and/or a length of time that the user will participate in a current and/or subsequent dialog session with the automated assistant. A user request can be compiled from content of an ongoing spoken utterance and content of any selected suggestion elements. When a currently compiled portion of the user request (from content of a selected suggestion(s) and an incomplete spoken utterance) is capable of being performed via the automated assistant, any actions corresponding to the currently compiled portion of the user request can be performed via the automated assistant. Furthermore, any further content resulting from performance of the actions, along with any discernible context, can be used for providing further suggestions.

    Acoustic model training using corrected terms

    公开(公告)号:US11200887B2

    公开(公告)日:2021-12-14

    申请号:US16837393

    申请日:2020-04-01

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for speech recognition. One of the methods includes receiving first audio data corresponding to an utterance; obtaining a first transcription of the first audio data; receiving data indicating (i) a selection of one or more terms of the first transcription and (ii) one or more of replacement terms; determining that one or more of the replacement terms are classified as a correction of one or more of the selected terms; in response to determining that the one or more of the replacement terms are classified as a correction of the one or more of the selected terms, obtaining a first portion of the first audio data that corresponds to one or more terms of the first transcription; and using the first portion of the first audio data that is associated with the one or more terms of the first transcription to train an acoustic model for recognizing the one or more of the replacement terms.

    ACOUSTIC MODEL TRAINING USING CORRECTED TERMS

    公开(公告)号:US20200243070A1

    公开(公告)日:2020-07-30

    申请号:US16837393

    申请日:2020-04-01

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for speech recognition. One of the methods includes receiving first audio data corresponding to an utterance; obtaining a first transcription of the first audio data; receiving data indicating (i) a selection of one or more terms of the first transcription and (ii) one or more of replacement terms; determining that one or more of the replacement terms are classified as a correction of one or more of the selected terms; in response to determining that the one or more of the replacement terms are classified as a correction of the one or more of the selected terms, obtaining a first portion of the first audio data that corresponds to one or more terms of the first transcription; and using the first portion of the first audio data that is associated with the one or more terms of the first transcription to train an acoustic model for recognizing the one or more of the replacement terms.

    ACOUSTIC MODEL TRAINING USING CORRECTED TERMS

    公开(公告)号:US20180308471A1

    公开(公告)日:2018-10-25

    申请号:US16023658

    申请日:2018-06-29

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for speech recognition. One of the methods includes receiving first audio data corresponding to an utterance; obtaining a first transcription of the first audio data; receiving data indicating (i) a selection of one or more terms of the first transcription and (ii) one or more of replacement terms; determining that one or more of the replacement terms are classified as a correction of one or more of the selected terms; in response to determining that the one or more of the replacement terms are classified as a correction of the one or more of the selected terms, obtaining a first portion of the first audio data that corresponds to one or more terms of the first transcription; and using the first portion of the first audio data that is associated with the one or more terms of the first transcription to train an acoustic model for recognizing the one or more of the replacement terms.

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