Signal-Based Performance Evaluation of Dereverberation Algorithms

Author:

Naylor Patrick A.1ORCID,Gaubitch Nikolay D.1,Habets Emanuël A. P.1ORCID

Affiliation:

1. Communications and Signal Processing Group, Department of Electrical and Electronic Engineering, Imperial College, London SW7 2AZ, UK

Abstract

We address the measurement of reverberation in terms of the (DRR) in the context of the assessment of dereverberation algorithms for which we wish to quantify the level of reverberation before and after processing. The DRR is normally calculated from the impulse response of the reverberating system. However, several important dereverberation algorithms involve nonlinear and/or time-varying processing and therefore their effect cannot conveniently be represented in terms of modifications to the impulse response of the reverberating system. In such cases, we show that a good estimate of DRR can be obtained from the input/output signals alone using the Signal-to-Reverberant Ratio (SRR) only if the source signal is spectrally white and correctly normalized. We study alternative normalization schemes and conclude by showing a least squares optimal normalization procedure for estimating DRR using signal-based SRR measurement. Simulation results illustrate the accuracy of DRR estimation using SRR.

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,General Computer Science,Signal Processing

Cited by 23 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Signal Compaction Using Polynomial EVD for Spherical Array Processing With Applications;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2023

2. Relative Acoustic Features for Distance Estimation in Smart-Homes;Interspeech 2022;2022-09-18

3. Adaptive Dereverberation, Noise and Interferer Reduction Using Sparse Weighted Linearly Constrained Minimum Power Beamforming;2022 30th European Signal Processing Conference (EUSIPCO);2022-08-29

4. Polynomial Matrix Eigenvalue Decomposition of Spherical Harmonics for Speech Enhancement;ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2021-06-06

5. Enhancement of Noisy Reverberant Speech Using Polynomial Matrix Eigenvalue Decomposition;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3