Google Inc.

David Rybach

Tara N Sainath

Yonghui Wu

Ruoming Pang

Rohit Prakash Prabhavalkar

Trevor D Strohman

Chung-Cheng Chiu

Yanzhang He

Wei Li

Ian C McGraw

Li Wei

Qiao Liang

Mirkó Visontai

Tara C Sainath

Ian C Mcgraw

Basilio Castillo Garcia

Two-pass automatic speech recognition (ASR) models can be used to perform streaming on-device ASR to generate a text representation of an utterance captured in audio data. Various implementations include a first-pass portion of the ASR model used to generate streaming candidate recognition(s) of an utterance captured in audio data. For example, the first-pass portion can include a recurrent neural network transformer (RNN-T) decoder. Various implementations include a second-pass portion of the ASR model used to revise the streaming candidate recognition(s) of the utterance and generate a text representation of the utterance. For example, the second-pass portion can include a listen attend spell (LAS) decoder. Various implementations include a shared encoder shared between the RNN-T decoder and the LAS decoder.

Two-pass end to end speech recognition

Growing community of inventors

Mountain View, CA, United States of America

David Rybach