most citedUNetGAN: A Robust Speech Enhancement Approach in Time Domain for Extremely Low Signal-to-noise Ratio Condition

41 citations · 43 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SD20222 cited

Coarse-to-Fine Recursive Speech Separation for Unknown Number of Speakers

Zhenhao Jin, Xiang Hao, Xiangdong Su

The vast majority of speech separation methods assume that the number of speakers is known in advance, hence they are specific to the number of speakers. By contrast, a more realis…

eess.AS202041 cited

UNetGAN: A Robust Speech Enhancement Approach in Time Domain for Extremely Low Signal-to-noise Ratio Condition

Xiang Hao, Xiangdong Su, Zhiyu Wang +2

Speech enhancement at extremely low signal-to-noise ratio (SNR) condition is a very challenging problem and rarely investigated in previous works. This paper proposes a robust spee…

cs.CV2020

An Edge Information and Mask Shrinking Based Image Inpainting Approach

Huali Xu, Xiangdong Su, Meng Wang +2

In the image inpainting task, the ability to repair both high-frequency and low-frequency information in the missing regions has a substantial influence on the quality of the resto…

eess.AS2020

SNR-Based Teachers-Student Technique for Speech Enhancement

Xiang Hao, Xiangdong Su, Zhiyu Wang +3

It is very challenging for speech enhancement methods to achieves robust performance under both high signal-to-noise ratio (SNR) and low SNR simultaneously. In this paper, we propo…

eess.AS2020

Sub-Band Knowledge Distillation Framework for Speech Enhancement

Xiang Hao, Shixue Wen, Xiangdong Su +3

In single-channel speech enhancement, methods based on full-band spectral features have been widely studied. However, only a few methods pay attention to non-full-band spectral fea…