Building a text-to-speech system from a small amount of speech data

    公开(公告)号:US11335321B2

    公开(公告)日:2022-05-17

    申请号:US17005974

    申请日:2020-08-28

    Applicant: Google LLC

    Abstract: A method of building a text-to-speech (TTS) system from a small amount of speech data includes receiving a first plurality of recorded speech samples from an assortment of speakers and a second plurality of recorded speech samples from a target speaker where the assortment of speakers does not include the target speaker. The method further includes training a TTS model using the first plurality of recorded speech samples from the assortment of speakers. Here, the trained TTS model is configured to output synthetic speech as an audible representation of a text input. The method also includes re-training the trained TTS model using the second plurality of recorded speech samples from the target speaker combined with the first plurality of recorded speech samples from the assortment of speakers. Here, the re-trained TTS model is configured to output synthetic speech resembling speaking characteristics of the target speaker.

    Building a Text-to-Speech System from a Small Amount of Speech Data

    公开(公告)号:US20220068256A1

    公开(公告)日:2022-03-03

    申请号:US17005974

    申请日:2020-08-28

    Applicant: Google LLC

    Abstract: A method of building a text-to-speech (TTS) system from a small amount of speech data includes receiving a first plurality of recorded speech samples from an assortment of speakers and a second plurality of recorded speech samples from a target speaker where the assortment of speakers does not include the target speaker. The method further includes training a TTS model using the first plurality of recorded speech samples from the assortment of speakers. Here, the trained TTS model is configured to output synthetic speech as an audible representation of a text input. The method also includes re-training the trained TTS model using the second plurality of recorded speech samples from the target speaker combined with the first plurality of recorded speech samples from the assortment of speakers. Here, the re-trained TTS model is configured to output synthetic speech resembling speaking characteristics of the target speaker.

    SYSTEMS AND METHODS FOR NEAREST-NEIGHBOR PREDICTION BASED MACHINE LEARNED MODELS

    公开(公告)号:US20220245917A1

    公开(公告)日:2022-08-04

    申请号:US17559633

    申请日:2021-12-22

    Applicant: Google LLC

    Abstract: Systems and methods of the present disclosure can include a computer-implemented method. The method can include obtaining a machine-learned model comprising one or more layers. At least a first layer of the one or more layers can be configured to receive a set of query vectors respectively associated with layer inputs, determine similarity measures the key vectors and the query vectors, apply a normalization operation to the plurality of respective similarity measures, and determine an output based on the normalized respective similarity measures and a plurality of class labels respectively associated with the plurality of key vectors.

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