Speech dereverberation using weighted prediction error with prior learnt from data

Ziye Yang, Wenxing Yang, Kai Xie, Jie Chen

科研成果: 书/报告/会议事项章节会议稿件同行评审

4 引用 (Scopus)

摘要

Speech dereverberation aims to mitigate the impact of late-reverberant components. As a typical approach to dereverberation, the weighted prediction error (WPE) method has shown its superior performance, however it is still possible to further improve its performance and robustness by incorporating sophisticated speech priors. Recent research demonstrates that the integration of physics-based and data-driven methods can improve the performance of various signal processing tasks while maintaining the interpretability of the problem solving process. Motivated by the relevant progress, this paper presents a novel dereverberation framework that incorporates the data-driven method for speech prior capturing for WPE. The plug-and-play strategy (PnP), specifically the regularization by denoising (RED) strategy, is used to incorporate speech prior information during the alternating direction method of multipliers (ADMM) solving iterations by plugging in a pre-trained speech denoiser. Experimental results demonstrate the effectiveness of the proposed method.

源语言英语
主期刊名31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings
出版商European Signal Processing Conference, EUSIPCO
356-360
页数5
ISBN(电子版)9789464593600
DOI
出版状态已出版 - 2023
活动31st European Signal Processing Conference, EUSIPCO 2023 - Helsinki, 芬兰
期限: 4 9月 20238 9月 2023

出版系列

姓名European Signal Processing Conference
ISSN(印刷版)2219-5491

会议

会议31st European Signal Processing Conference, EUSIPCO 2023
国家/地区芬兰
Helsinki
时期4/09/238/09/23

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