activity
20172022
most citedEnd-to-End Multi-Channel Speech Separation

80 citations · 242 across the 20 of their papers we have counts for

collaborators

34 papers

cs.SD20221 cited

Neural Sound Field Decomposition with Super-resolution of Sound Direction

Qiuqiang Kong, Shilei Liu, Junjie Shi +5

Sound field decomposition predicts waveforms in arbitrary directions using signals from a limited number of microphones as inputs. Sound field decomposition is fundamental to downs…

eess.AS20225 cited

NeuralEcho: A Self-Attentive Recurrent Neural Network For Unified Acoustic Echo Suppression And Speech Enhancement

Meng Yu, Yong Xu, Chunlei Zhang +2

Acoustic echo cancellation (AEC) plays an important role in the full-duplex speech communication as well as the front-end speech enhancement for recognition in the conditions when…

cs.SD20211 cited

MIMO Self-attentive RNN Beamformer for Multi-speaker Speech Separation

Xiyun Li, Yong Xu, Meng Yu +4

Recently, our proposed recurrent neural network (RNN) based all deep learning minimum variance distortionless response (ADL-MVDR) beamformer method yielded superior performance ove…

eess.AS20215 cited

MetricNet: Towards Improved Modeling For Non-Intrusive Speech Quality Assessment

Meng Yu, Chunlei Zhang, Yong Xu +2

The objective speech quality assessment is usually conducted by comparing received speech signal with its clean reference, while human beings are capable of evaluating the speech q…

eess.AS2021

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…

cs.SD2021

Generalized Spatio-Temporal RNN Beamformer for Target Speech Separation

Yong Xu, Zhuohuang Zhang, Meng Yu +2

Although the conventional mask-based minimum variance distortionless response (MVDR) could reduce the non-linear distortion, the residual noise level of the MVDR separated speech i…