Joint unsupervised and supervised training for multilingual ASR

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United States of America

PATENT NO 12249317
APP PUB NO 20230104228A1
SERIAL NO

17929934

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Abstract

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A method includes receiving audio features and generating a latent speech representation based on the audio features. The method also includes generating a target quantized vector token and a target token index for a corresponding latent speech representation. The method also includes generating a contrastive context vector for a corresponding unmasked or masked latent speech representation and deriving a contrastive self-supervised loss based on the corresponding contrastive context vector and the corresponding target quantized vector token. The method also include generating a high-level context vector based on the contrastive context vector and, for each high-level context vector, learning to predict the target token index at the corresponding time step using a cross-entropy loss based on the target token index. The method also includes predicting speech recognition hypotheses for the utterance and training a multilingual automatic speech recognition (ASR) model using an unsupervised loss and a supervised loss.

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Patent Owner(s)

  • GOOGLE LLC

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Bai, Junwen Mountain View, US 4 5
Bapna, Ankur Sunnyvale, US 12 89
Li, Bo Fremont, US 785 4905
Sainath, Tara N Jersey City, US 180 3361
Siddhartha, Nikhil Mountain View, US 2 9
Sim, Khe Chai Dublin, US 20 39
Zhang, Yu Mountain View, US 1971 9206

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