A dual-stream deep attractor network with multi-domain learning for speech dereverberation and separation

Author:

Chen HangtingORCID,Zhang PengyuanORCID

Funder

National Natural Science Foundation of China

Chinese Academy of Sciences

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience

Reference43 articles.

1. Bahmaninezhad, F., Wu, J. Y., Gu, R., Zhang, S.-X., Xu, Y., & Yu, M., et al. (2019). A comprehensive study of speech separation: spectrogram vs waveform separation. In INTERSPEECH.

2. On the importance of early reflections for speech in rooms;Bradley;The Journal of the Acoustical Society of America,2003

3. SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition;Drude,2019

4. A regression approach to single-channel speech separation via high-resolution deep neural networks;Du;IEEE/ACM Transactions on Audio, Speech, and Language Processing,2016

5. Simultaneous denoising and dereverberation using deep embedding features;Fan,2020

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