2 citations · 6 across the 7 of their papers we have counts for
6 papers · 1 filter
RealMAN: A Real-Recorded and Annotated Microphone Array Dataset for Dynamic Speech Enhancement and Localization
Bing Yang, Changsheng Quan, Yabo Wang +7
The training of deep learning-based multichannel speech enhancement and source localization systems relies heavily on the simulation of room impulse response and multichannel diffu…
Multichannel Long-Term Streaming Neural Speech Enhancement for Static and Moving Speakers
Changsheng Quan, Xiaofei Li
In this work, we extend our previously proposed offline SpatialNet for long-term streaming multichannel speech enhancement in both static and moving speaker scenarios. SpatialNet e…
SpatialNet: Extensively Learning Spatial Information for Multichannel Joint Speech Separation, Denoising and Dereverberation
Changsheng Quan, Xiaofei Li
This work proposes a neural network to extensively exploit spatial information for multichannel joint speech separation, denoising and dereverberation, named SpatialNet. In the sho…
NBC2: Multichannel Speech Separation with Revised Narrow-band Conformer
Changsheng Quan, Xiaofei Li
This work proposes a multichannel narrow-band speech separation network. In the short-time Fourier transform (STFT) domain, the proposed network processes each frequency independen…
Multichannel Speech Separation with Narrow-band Conformer
Changsheng Quan, Xiaofei Li
This work proposes a multichannel speech separation method with narrow-band Conformer (named NBC). The network is trained to learn to automatically exploit narrow-band speech separ…
Multi-channel Narrow-band Deep Speech Separation with Full-band Permutation Invariant Training
Changsheng Quan, Xiaofei Li
This paper addresses the problem of multi-channel multi-speech separation based on deep learning techniques. In the short time Fourier transform domain, we propose an end-to-end na…