A distortionless convolution beamformer design method based on the weighted minimum mean square error for joint dereverberation and denoising

IF 2.4 3区计算机科学 Q2 ACOUSTICS

Speech Communication Pub Date : 2024-03-01 DOI:10.1016/j.specom.2024.103054

Jing Zhou, Changchun Bao, Maoshen Jia, Wenmeng Xiong

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引用次数: 0

Abstract

This paper designs a weighted minimum mean square error (WMMSE) based distortionless convolution beamformer (DCBF) for joint dereverberation and denoising. By effectively using WMMSE with the constraint of distortionless, a DCBF is deduced, where the outputs of the weighted prediction error (WPE) filter and the WPE-based minimum variance distortionless response (MVDR) beamformer are combined to initialize target signal for balancing signal distortion, residual reverberation and residual noise. In addition, two optimization factors are introduced to reduce the reverberation and noise when the initialized target signal is used for the solution of beamformer. As a result, the designed beamformer is presented as a linear combination of the WMMSE-based convolution beamformer (CBF) and weighted power minimization distortionless response (WPD) filter. The experimental results demonstrate the superior performance of the designed beamformer for joint dereverberation and denoising compared to the reference methods.

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基于加权最小均方误差的无失真卷积波束成形器设计方法，用于联合消除混响和去噪

本文设计了一种基于加权最小均方误差（WMMSE）的无失真卷积波束成形器（DCBF），用于联合消除混响和去噪。通过有效利用 WMMSE 和无失真约束，推导出一种 DCBF，将加权预测误差（WPE）滤波器和基于 WPE 的最小方差无失真响应（MVDR）波束成形器的输出结合起来，对目标信号进行初始化，以平衡信号失真、残余混响和残余噪声。此外，在将初始化目标信号用于波束成形器求解时，还引入了两个优化因子来降低混响和噪声。因此，所设计的波束成形器是基于 WMMSE 的卷积波束成形器（CBF）和加权功率最小化无失真响应滤波器（WPD）的线性组合。实验结果表明，与参考方法相比，所设计的波束成形器在联合去混响和去噪方面性能优越。

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来源期刊

Speech Communication 工程技术-计算机：跨学科应用

CiteScore

6.80

自引率

6.20%

发文量

审稿时长

19.2 weeks

期刊介绍： Speech Communication is an interdisciplinary journal whose primary objective is to fulfil the need for the rapid dissemination and thorough discussion of basic and applied research results. The journal''s primary objectives are: • to present a forum for the advancement of human and human-machine speech communication science; • to stimulate cross-fertilization between different fields of this domain; • to contribute towards the rapid and wide diffusion of scientifically sound contributions in this domain.