基于神经掩模的多通道卷积波束形成联合去噪、回波抵消和去噪

Jianming Liu, Meng Yu, Yong Xu, Chao Weng, Shi-Xiong Zhang, Lianwu Chen, Dong Yu
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引用次数: 3

摘要

本文提出了一种新的同时去噪、回声消除和去噪的联合优化框架,该框架是由最近提出的同时去噪和去噪的卷积波束形成器驱动的。该算法采用基于回波感知掩模的波束形成框架,能够有效地处理双话情况和局部推理等问题。基于ERLE和PESQ的双通测试结果表明,该算法可以显著提高系统性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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.
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