Deferred NAM: Low-latency Top-K Context Injection via DeferredContext Encoding for Non-Streaming ASR

no code implementations • 15 Apr 2024 • Zelin Wu, Gan Song, Christopher Li, Pat Rondon, Zhong Meng, Xavier Velez, Weiran Wang, Diamantino Caseiro, Golan Pundak, Tsendsuren Munkhdalai, Angad Chandorkar, Rohit Prabhavalkar

Contextual biasing enables speech recognizers to transcribe important phrases in the speaker's context, such as contact names, even if they are rare in, or absent from, the training data.

Fast Contextual Adaptation with Neural Associative Memory for On-Device Personalized Speech Recognition

no code implementations • 5 Oct 2021 • Tsendsuren Munkhdalai, Khe Chai Sim, Angad Chandorkar, Fan Gao, Mason Chua, Trevor Strohman, Françoise Beaufays

Fast contextual adaptation has shown to be effective in improving Automatic Speech Recognition (ASR) of rare words and when combined with an on-device personalized training, it can yield an even better recognition result.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

On-Device Personalization of Automatic Speech Recognition Models for Disordered Speech

no code implementations • 18 Jun 2021 • Katrin Tomanek, Françoise Beaufays, Julie Cattiau, Angad Chandorkar, Khe Chai Sim

While current state-of-the-art Automatic Speech Recognition (ASR) systems achieve high accuracy on typical speech, they suffer from significant performance degradation on disordered speech and other atypical speech patterns.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1