NDLI: Multichannel noise reduction in the Karhunen-Loève expansion domain

Content Provider	ACM Digital Library
Author	Benesty, Jacob Habets, Emanuël A. P. Chen, Jingdong Lacouture-parodi, Yesenia
Copyright Year	2014
Abstract	The noise reduction problem is traditionally approached in the time, frequency, or transform domain. Having a signal dependent transform has shown some advantages over the traditional signal independent transform. Recently, the single-channel noise reduction problem in the Karhunen-Loève expansion (KLE) domain has received special attention. In this paper, the noise reduction problem in the KLE domain is studied from a multichannel perspective. We present a new formulation of the problem, in which inter-channel and inter-mode correlations are optimally exploited. We derive different optimal noise reduction filters and present a set of useful performance measures within this framework. The performance of the different filters is then evaluated through experiments in which not only noise but also competing speech sources are present. It is shown that the proposed multichannel formulation is more robust to competing speech sources than the single-channel approach and that a better compromise between noise reduction and speech distortion can be obtained.
Starting Page	923
Ending Page	936
Page Count	14
File Format	PDF
ISSN	23299290
e-ISSN	23299304
DOI	10.1109/TASLP.2014.2311299
Volume Number	22
Issue Number	5
Journal	IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-05-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Karhunen-Loève expansion (KLE) Maximum snr filter Minimum variance distortionless response (MVDR) filter Multichannel Noise reduction Speech enhancement Tradeoff filter Wiener filter
Content Type	Text
Resource Type	Article
Subject	Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology

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