no code implementations • 18 May 2023 • Yanjie Fu, Meng Ge, Honglong Wang, Nan Li, Haoran Yin, Longbiao Wang, Gaoyan Zhang, Jianwu Dang, Chengyun Deng, Fei Wang
Recently, stunning improvements on multi-channel speech separation have been achieved by neural beamformers when direction information is available.
no code implementations • 7 Dec 2022 • Yanjie Fu, Haoran Yin, Meng Ge, Longbiao Wang, Gaoyan Zhang, Jianwu Dang, Chengyun Deng, Fei Wang
Recently, many deep learning based beamformers have been proposed for multi-channel speech separation.
no code implementations • 4 Nov 2020 • Chengyun Deng, Shiqian Ma, Yi Zhang, Yongtao Sha, HUI ZHANG, Hui Song, Xiangang Li
dataset confirm the superior performance of the proposed method over the network without IRA in terms of SI-SDR and PESQ improvement.
no code implementations • 4 Nov 2020 • Yi Zhang, Chengyun Deng, Shiqian Ma, Yongtao Sha, Hui Song
In this paper, a multi-task network is proposed to address both ref-delay estimation and echo cancellation tasks.
no code implementations • 29 Jul 2020 • Zhuohuang Zhang, Chengyun Deng, Yi Shen, Donald S. Williamson, Yongtao Sha, Yi Zhang, Hui Song, Xiangang Li
Recent work has shown that it is feasible to use generative adversarial networks (GANs) for speech enhancement, however, these approaches have not been compared to state-of-the-art (SOTA) non GAN-based approaches.
Audio and Speech Processing Sound