8 citations · 10 across the 4 of their papers we have counts for
5 papers
Locate and Beamform: Two-dimensional Locating All-neural Beamformer for Multi-channel Speech Separation
Yanjie Fu, Meng Ge, Honglong Wang +7
Recently, stunning improvements on multi-channel speech separation have been achieved by neural beamformers when direction information is available. However, most of them neglect t…
MIMO-DBnet: Multi-channel Input and Multiple Outputs DOA-aware Beamforming Network for Speech Separation
Yanjie Fu, Haoran Yin, Meng Ge +5
Recently, many deep learning based beamformers have been proposed for multi-channel speech separation. Nevertheless, most of them rely on extra cues known in advance, such as speak…
Deep Multi-task Network for Delay Estimation and Echo Cancellation
Yi Zhang, Chengyun Deng, Shiqian Ma +2
Echo path delay (or ref-delay) estimation is a big challenge in acoustic echo cancellation. Different devices may introduce various ref-delay in practice. Ref-delay inconsistency s…
Robust Speaker Extraction Network Based on Iterative Refined Adaptation
Chengyun Deng, Shiqian Ma, Yi Zhang +4
Speaker extraction aims to extract target speech signal from a multi-talker environment with interference speakers and surrounding noise, given the target speaker's reference infor…
On Loss Functions and Recurrency Training for GAN-based Speech Enhancement Systems
Zhuohuang Zhang, Chengyun Deng, Yi Shen +5
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…