MULTI-DIALECT AND MULTILINGUAL SPEECH RECOGNITION

    公开(公告)号:US20220130374A1

    公开(公告)日:2022-04-28

    申请号:US17572238

    申请日:2022-01-10

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.

    Multi-dialect and multilingual speech recognition

    公开(公告)号:US11238845B2

    公开(公告)日:2022-02-01

    申请号:US16684483

    申请日:2019-11-14

    Applicant: GOOGLE LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.

    MULTI-DIALECT AND MULTILINGUAL SPEECH RECOGNITION

    公开(公告)号:US20200160836A1

    公开(公告)日:2020-05-21

    申请号:US16684483

    申请日:2019-11-14

    Applicant: GOOGLE LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.

    Multi-dialect and multilingual speech recognition

    公开(公告)号:US12254865B2

    公开(公告)日:2025-03-18

    申请号:US18418246

    申请日:2024-01-20

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-readable media, for speech recognition using multi-dialect and multilingual models. In some implementations, audio data indicating audio characteristics of an utterance is received. Input features determined based on the audio data are provided to a speech recognition model that has been trained to output score indicating the likelihood of linguistic units for each of multiple different language or dialects. The speech recognition model can be one that has been trained using cluster adaptive training. Output that the speech recognition model generated in response to receiving the input features determined based on the audio data is received. A transcription of the utterance generated based on the output of the speech recognition model is provided.

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