113 citations · 179 across the 33 of their papers we have counts for
6 papers · 1 filter
Fast Contextual Adaptation with Neural Associative Memory for On-Device Personalized Speech Recognition
Tsendsuren Munkhdalai, Khe Chai Sim, Angad Chandorkar +4
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…
Input Length Matters: Improving RNN-T and MWER Training for Long-form Telephony Speech Recognition
Zhiyun Lu, Yanwei Pan, Thibault Doutre +5
End-to-end models have achieved state-of-the-art results on several automatic speech recognition tasks. However, they perform poorly when evaluated on long-form data, e.g., minutes…
Large-scale ASR Domain Adaptation using Self- and Semi-supervised Learning
Dongseong Hwang, Ananya Misra, Zhouyuan Huo +7
Self- and semi-supervised learning methods have been actively investigated to reduce labeled training data or enhance the model performance. However, the approach mostly focus on i…
Incremental Layer-wise Self-Supervised Learning for Efficient Speech Domain Adaptation On Device
Zhouyuan Huo, Dongseong Hwang, Khe Chai Sim +5
Streaming end-to-end speech recognition models have been widely applied to mobile devices and show significant improvement in efficiency. These models are typically trained on the…
Lookup-Table Recurrent Language Models for Long Tail Speech Recognition
W. Ronny Huang, Tara N. Sainath, Cal Peyser +3
We introduce Lookup-Table Language Models (LookupLM), a method for scaling up the size of RNN language models with only a constant increase in the floating point operations, by inc…
Transformer Based Deliberation for Two-Pass Speech Recognition
Ke Hu, Ruoming Pang, Tara N. Sainath +1
Interactive speech recognition systems must generate words quickly while also producing accurate results. Two-pass models excel at these requirements by employing a first-pass deco…