Neural Mask based Multi-channel Convolutional Beamforming for Joint Dereverberation, Echo Cancellation and Denoising
| Autor: | Shi-Xiong Zhang, Yong Xu, Lianwu Chen, Jianming Liu, Meng Yu, Dong Yu, Chao Weng |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Beamforming
Computer science Speech recognition Noise reduction Echo (computing) Inference 020206 networking & telecommunications 02 engineering and technology 030507 speech-language pathology & audiology 03 medical and health sciences Computer Science::Sound 0202 electrical engineering electronic engineering information engineering ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS 0305 other medical science Joint (audio engineering) Multi channel PESQ |
| Zdroj: | SLT |
| DOI: | 10.1109/slt48900.2021.9383519 |
| Popis: | This paper proposes a new joint optimization framework for simultaneous dereverberation, acoustic echo cancellation, and denoising, which is motivated by the recently proposed con-volutional beamformer for simultaneous denoising and dereverberation. Using the echo aware mask based beamforming framework, the proposed algorithm could effectively deal with double-talk case and local inference, etc. The evaluations based on ERLE for echo only, and PESQ for double-talk demonstrate that the proposed algorithm could significantly improve the performance. |
| Databáze: | OpenAIRE |
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