activity
20192022
most citedEnd-to-End Multi-Channel Speech Separation

80 citations · 199 across the 17 of their papers we have counts for

collaborators

23 papers

cs.CL2022

Multilingual Transformer Language Model for Speech Recognition in Low-resource Languages

Li Miao, Jian Wu, Piyush Behre +2

It is challenging to train and deploy Transformer LMs for hybrid speech recognition 2nd pass re-ranking in low-resource languages due to (1) data scarcity in low-resource languages…

cs.SD20222 cited

Deploying self-supervised learning in the wild for hybrid automatic speech recognition

Mostafa Karimi, Changliang Liu, Kenichi Kumatani +3

Self-supervised learning (SSL) methods have proven to be very successful in automatic speech recognition (ASR). These great improvements have been reported mostly based on highly c…

eess.AS202215 cited

Ultra Fast Speech Separation Model with Teacher Student Learning

Sanyuan Chen, Yu Wu, Zhuo Chen +5

Transformer has been successfully applied to speech separation recently with its strong long-dependency modeling capacity using a self-attention mechanism. However, Transformer ten…

eess.AS2021

Continuous Speech Separation with Recurrent Selective Attention Network

Yixuan Zhang, Zhuo Chen, Jian Wu +4

While permutation invariant training (PIT) based continuous speech separation (CSS) significantly improves the conversation transcription accuracy, it often suffers from speech lea…

cs.CL202110 cited

UniSpeech-SAT: Universal Speech Representation Learning with Speaker Aware Pre-Training

Sanyuan Chen, Yu Wu, Chengyi Wang +8

Self-supervised learning (SSL) is a long-standing goal for speech processing, since it utilizes large-scale unlabeled data and avoids extensive human labeling. Recent years witness…

eess.AS2021

Investigation of Practical Aspects of Single Channel Speech Separation for ASR

Jian Wu, Zhuo Chen, Sanyuan Chen +5

Speech separation has been successfully applied as a frontend processing module of conversation transcription systems thanks to its ability to handle overlapped speech and its flex…