Noise Robust Blind System Identification Algorithms Based On A Rayleigh Quotient Cost Function
File(s)
Accepted version
Author(s)
Hu, M
Doclo, S
Sharma, D
Brookes, D
Naylor, P
Type
Conference Paper
Abstract
An important prerequisite for acoustic multi-channel equalization for speech dereverberation involves the identification of the acoustic channels between the source and the microphones. Blind System Identification (BSI) algorithms based on cross-relation error minimization are known to mis-converge in the presence of noise. Although algorithms have been proposed in the literature to improve robustness to noise, the estimated room impulse responses are usually constrained to have a flat magnitude spectrum. In this paper, noise robust algorithms based on a Rayleigh quotient cost function are proposed. Unlike the traditional algorithms, the estimated impulse responses are not always forced to have unit norm. Experimental results using simulated room impulse responses and several SNRs show that one of the proposed algorithms outperforms competing algorithms in terms of normalized projection misalignment.
Date Issued
2015-09-04
Date Acceptance
2015-05-22
Citation
2015 23rd European Signal Processing Conference (EUSIPCO), 2015, pp.2476-2480
Publisher
IEEE
Start Page
2476
End Page
2480
Journal / Book Title
2015 23rd European Signal Processing Conference (EUSIPCO)
Copyright Statement
© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Source
European Signal Processing Conference (EUSIPCO)
Publication Status
Published
Start Date
2015-08-31
Finish Date
2015-09-04
Coverage Spatial
Nice