Sound model localization within an environment

    公开(公告)号:US12073319B2

    公开(公告)日:2024-08-27

    申请号:US16940294

    申请日:2020-07-27

    Applicant: GOOGLE LLC

    CPC classification number: G06N3/08 G06N3/047 G10L25/51

    Abstract: Systems and techniques are provided for sound model localization within an environment. Sound recordings of sounds in the environment may be received from devices in the environment. Preliminary labels for the sound recordings may be determined using pre-trained sound models. The preliminary labels may have associated probabilities. Sound clips with preliminary labels may be generated based on sound recordings that have preliminary labels whose probability is over a high-recall threshold for the pre-trained sound model that determined the preliminary label. The sound clips with preliminary labels may be sent to a user device. Labeled sound clips may be received from the user device. The labeled sound clips may be based on the sound clips with preliminary labels. Training data sets may be generated for the pre-trained sound models using the labeled sound clips. The pre-trained sound models may be trained using the training data sets to generate localized sound models.

    SOUND MODEL LOCALIZATION WITHIN AN ENVIRONMENT

    公开(公告)号:US20220027725A1

    公开(公告)日:2022-01-27

    申请号:US16940294

    申请日:2020-07-27

    Applicant: GOOGLE LLC

    Abstract: Systems and techniques are provided for sound model localization within an environment. Sound recordings of sounds in the environment may be received from devices in the environment. Preliminary labels for the sound recordings may be determined using pre-trained sound models. The preliminary labels may have associated probabilities. Sound clips with preliminary labels may be generated based on sound recordings that have preliminary labels whose probability is over a high-recall threshold for the pre-trained sound model that determined the preliminary label. The sound clips with preliminary labels may be sent to a user device. Labeled sound clips may be received from the user device. The labeled sound clips may be based on the sound clips with preliminary labels. Training data sets may be generated for the pre-trained sound models using the labeled sound clips. The pre-trained sound models may be trained using the training data sets to generate localized sound models.

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