477 citations · 1.7k across the 84 of their papers we have counts for
8 papers · 2 filters
Overlapped speech recognition from a jointly learned multi-channel neural speech extraction and representation
Bo Wu, Meng Yu, Lianwu Chen +3
We propose an end-to-end joint optimization framework of a multi-channel neural speech extraction and deep acoustic model without mel-filterbank (FBANK) extraction for overlapped s…
DFSMN-SAN with Persistent Memory Model for Automatic Speech Recognition
Zhao You, Dan Su, Jie Chen +2
Self-attention networks (SAN) have been introduced into automatic speech recognition (ASR) and achieved state-of-the-art performance owing to its superior ability in capturing long…
Mixup-breakdown: a consistency training method for improving generalization of speech separation models
Max W. Y. Lam, Jun Wang, Dan Su +1
Deep-learning based speech separation models confront poor generalization problem that even the state-of-the-art models could abruptly fail when evaluating them in mismatch conditi…
Audio-Visual Speech Separation and Dereverberation with a Two-Stage Multimodal Network
Ke Tan, Yong Xu, Shi-Xiong Zhang +2
Background noise, interfering speech and room reverberation frequently distort target speech in real listening environments. In this study, we address joint speech separation and d…
Maximizing Mutual Information for Tacotron
Peng Liu, Xixin Wu, Shiyin Kang +3
End-to-end speech synthesis methods already achieve close-to-human quality performance. However compared to HMM-based and NN-based frame-to-frame regression methods, they are prone…
Teach an all-rounder with experts in different domains
Zhao You, Dan Su, Dong Yu
In many automatic speech recognition (ASR) tasks, an ideal model has to be applicable over multiple domains. In this paper, we propose to teach an all-rounder with experts in diffe…
Improved Speaker-Dependent Separation for CHiME-5 Challenge
Jian Wu, Yong Xu, Shi-Xiong Zhang +4
This paper summarizes several follow-up contributions for improving our submitted NWPU speaker-dependent system for CHiME-5 challenge, which aims to solve the problem of multi-chan…
Time Domain Audio Visual Speech Separation
Jian Wu, Yong Xu, Shi-Xiong Zhang +4
Audio-visual multi-modal modeling has been demonstrated to be effective in many speech related tasks, such as speech recognition and speech enhancement. This paper introduces a new…