Neural Mask Based Multi-Channel Convolutional Beamforming For Joint Dereverberation, Echo Cancellation And Denoising

This paper proposes a new joint optimization framework for simultaneous dereverberation, acoustic echo cancellation, and denoising, which is motivated by the recently proposed convolutional 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.