Conferencingspeech Challenge: Towards Far-Field Multi-Channel Speech Enhancement for Video Conferencing-Reference-Cited by-同舟云学术

Conferencingspeech Challenge: Towards Far-Field Multi-Channel Speech Enhancement for Video Conferencing

Published:2021-12-13 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)
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Author:

Rao Wei¹,Fu Yihui²,Hu Yanxin²,Xu Xin³,Jv Yvkai²,Han Jiangyu¹,Jiang Zhongjie¹,Xie Lei²,Wang Yannan¹,Watanabe Shinji⁴,Tan Zheng-Hua⁵,Bu Hui³,Yu Tao⁶,Shang Shidong¹

Affiliation:

1. Tencent Ethereal Audio Lab,China

2. Northwestern Polytechnical University,China

3. Beijing Shell Shell Technology Co., LTD.,China

4. Carnegie Mellon University,USA

5. Aalborg University,Denmark

6. Tencent Ethereal Audio Lab,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9687821/9687855/09688126.pdf?arnumber=9688126

Reference32 articles.

1. Real-Time Multi-Channel Speech Enhancement Based on Neural Network Masking with Attention Model

2. SRIB-LEAP Submission to Far-Field Multi-Channel Speech Enhancement Challenge for Video Conferencing

3. A Causal U-Net Based Neural Beamforming Network for Real-Time Multi-Channel Speech Enhancement

4. Gaussian density guided deep neural network for single-channel speech enhancement

5. An Attention-based Neural Network Approach for Single Channel Speech Enhancement

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