activity
20192022
most citedBridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling

4 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

eess.AS2022

Self-supervised learning with bi-label masked speech prediction for streaming multi-talker speech recognition

Zili Huang, Zhuo Chen, Naoyuki Kanda +6

Self-supervised learning (SSL), which utilizes the input data itself for representation learning, has achieved state-of-the-art results for various downstream speech tasks. However…

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.CL20203 cited

Efficient End-to-End Speech Recognition Using Performers in Conformers

Peidong Wang, DeLiang Wang

On-device end-to-end speech recognition poses a high requirement on model efficiency. Most prior works improve the efficiency by reducing model sizes. We propose to reduce the comp…

cs.SD2020

Speaker Separation Using Speaker Inventories and Estimated Speech

Peidong Wang, Zhuo Chen, DeLiang Wang +2

We propose speaker separation using speaker inventories and estimated speech (SSUSIES), a framework leveraging speaker profiles and estimated speech for speaker separation. SSUSIES…

eess.AS20194 cited

Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling

Peidong Wang, Ke Tan, DeLiang Wang

Monaural speech enhancement has made dramatic advances since the introduction of deep learning a few years ago. Although enhanced speech has been demonstrated to have better intell…