35 citations · 50 across the 9 of their papers we have counts for
9 papers
TeCANet: Temporal-Contextual Attention Network for Environment-Aware Speech Dereverberation
Helin Wang, Bo Wu, Lianwu Chen +7
In this paper, we exploit the effective way to leverage contextual information to improve the speech dereverberation performance in real-world reverberant environments. We propose…
WPD++: An Improved Neural Beamformer for Simultaneous Speech Separation and Dereverberation
Zhaoheng Ni, Yong Xu, Meng Yu +4
This paper aims at eliminating the interfering speakers' speech, additive noise, and reverberation from the noisy multi-talker speech mixture that benefits automatic speech recogni…
Audio-visual Multi-channel Integration and Recognition of Overlapped Speech
Jianwei Yu, Shi-Xiong Zhang, Bo Wu +6
Automatic speech recognition (ASR) technologies have been significantly advanced in the past few decades. However, recognition of overlapped speech remains a highly challenging tas…
Distortionless Multi-Channel Target Speech Enhancement for Overlapped Speech Recognition
Bo Wu, Meng Yu, Lianwu Chen +4
Speech enhancement techniques based on deep learning have brought significant improvement on speech quality and intelligibility. Nevertheless, a large gain in speech quality measur…
End-to-End Multi-Look Keyword Spotting
Meng Yu, Xuan Ji, Bo Wu +2
The performance of keyword spotting (KWS), measured in false alarms and false rejects, degrades significantly under the far field and noisy conditions. In this paper, we propose a…
Audio-visual Multi-channel Recognition of Overlapped Speech
Jianwei Yu, Bo Wu, Rongzhi Gu +7
Automatic speech recognition (ASR) of overlapped speech remains a highly challenging task to date. To this end, multi-channel microphone array data are widely used in state-of-the-…
Audio-visual Recognition of Overlapped speech for the LRS2 dataset
Jianwei Yu, Shi-Xiong Zhang, Jian Wu +7
Automatic recognition of overlapped speech remains a highly challenging task to date. Motivated by the bimodal nature of human speech perception, this paper investigates the use of…
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…
Improving Reverberant Speech Training Using Diffuse Acoustic Simulation
Zhenyu Tang, Lianwu Chen, Bo Wu +2
We present an efficient and realistic geometric acoustic simulation approach for generating and augmenting training data in speech-related machine learning tasks. Our physically-ba…