activity
20202024
most citedUltra Fast Speech Separation Model with Teacher Student Learning

15 citations · 50 across the 18 of their papers we have counts for

collaborators

19 papers

eess.AS2022

Exploring WavLM on Speech Enhancement

Hyungchan Song, Sanyuan Chen, Zhuo Chen +5

There is a surge in interest in self-supervised learning approaches for end-to-end speech encoding in recent years as they have achieved great success. Especially, WavLM showed sta…

cs.SD2022

LongFNT: Long-form Speech Recognition with Factorized Neural Transducer

Xun Gong, Yu Wu, Jinyu Li +4

Traditional automatic speech recognition~(ASR) systems usually focus on individual utterances, without considering long-form speech with useful historical information, which is mor…

cs.SD20222 cited

Joint Pre-Training with Speech and Bilingual Text for Direct Speech to Speech Translation

Kun Wei, Long Zhou, Ziqiang Zhang +5

Direct speech-to-speech translation (S2ST) is an attractive research topic with many advantages compared to cascaded S2ST. However, direct S2ST suffers from the data scarcity probl…

eess.AS20222 cited

Robust Data2vec: Noise-robust Speech Representation Learning for ASR by Combining Regression and Improved Contrastive Learning

Qiu-Shi Zhu, Long Zhou, Jie Zhang +3

Self-supervised pre-training methods based on contrastive learning or regression tasks can utilize more unlabeled data to improve the performance of automatic speech recognition (A…

cs.CL20223 cited

SpeechUT: Bridging Speech and Text with Hidden-Unit for Encoder-Decoder Based Speech-Text Pre-training

Ziqiang Zhang, Long Zhou, Junyi Ao +4

The rapid development of single-modal pre-training has prompted researchers to pay more attention to cross-modal pre-training methods. In this paper, we propose a unified-modal spe…

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…