公开(公告)号：US20210225362A1

公开(公告)日：2021-07-22

申请号：US17155010

申请日：2021-01-21

Applicant: Google LLC

Inventor： Tara N. Sainath ,  Ruorning Pang ,  Ron Weiss ,  Yanzhang He ,  Chung-Cheng Chiu ,  Trevor Strohman

IPC: G10L15/06 ,  G10L15/16 ,  G10L15/197 ,  G06N3/08

Abstract: A method includes receiving a training example for a listen-attend-spell (LAS) decoder of a two-pass streaming neural network model and determining whether the training example corresponds to a supervised audio-text pair or an unpaired text sequence. When the training example corresponds to an unpaired text sequence, the method also includes determining a cross entropy loss based on a log probability associated with a context vector of the training example. The method also includes updating the LAS decoder and the context vector based on the determined cross entropy loss.

公开(公告)号：US20220310062A1

公开(公告)日：2022-09-29

申请号：US17316198

申请日：2021-05-10

Applicant: Google LLC

Inventor： Tara Sainath ,  Arun Narayanan ,  Rami Botros ,  Yangzhang He ,  Ehsan Variani ,  Cyrill Allauzen ,  David Rybach ,  Ruorning Pang ,  Trevor Strohman

IPC: G10L15/06 ,  G10L15/02 ,  G10L15/30 ,  G10L15/22

Abstract: An ASR model includes a first encoder configured to receive a sequence of acoustic frames and generate a first higher order feature representation for a corresponding acoustic frame in the sequence of acoustic frames. The ASR model also includes a second encoder configured to receive the first higher order feature representation generated by the first encoder at each of the plurality of output steps and generate a second higher order feature representation for a corresponding first higher order feature frame. The ASR model also includes a decoder configured to receive the second higher order feature representation generated by the second encoder at each of the plurality of output steps and generate a first probability distribution over possible speech recognition hypothesis. The ASR model also includes a language model configured to receive the first probability distribution over possible speech hypothesis and generate a rescored probability distribution.