Modulation-domain multichannel Kalman filtering for speech enhancement

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Title: Modulation-domain multichannel Kalman filtering for speech enhancement
Author(s): Xue, W
Moore, A
Brookes, DM
Naylor, P
Item Type: Journal Article
Abstract: Compared with single-channel speech enhancement methods, multichannel methods can utilize spatial information to design optimal filters. Although some filters adaptively consider second-order signal statistics, the temporal evolution of the speech spectrum is usually neglected. By using linear prediction (LP) to model the inter-frame temporal evolution of speech, single-channel Kalman filtering (KF) based methods have been developed for speech enhancement. In this paper, we derive a multichannel KF (MKF) that jointly uses both interchannel spatial correlation and interframe temporal correlation for speech enhancement. We perform LP in the modulation domain, and by incorporating the spatial information, derive an optimal MKF gain in the short-time Fourier transform domain. We show that the proposed MKF reduces to the conventional multichannel Wiener filter if the LP information is discarded. Furthermore, we show that, under an appropriate assumption, the MKF is equivalent to a concatenation of the minimum variance distortion response beamformer and a single-channel modulation-domain KF and therefore present an alternative implementation of the MKF. Experiments conducted on a public head-related impulse response database demonstrate the effectiveness of the proposed method.
Publication Date: 7-Jun-2018
Date of Acceptance: 4-Jun-2018
URI: http://hdl.handle.net/10044/1/60712
DOI: https://dx.doi.org/10.1109/TASLP.2018.2845665
ISSN: 2329-9290
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 1833
End Page: 1847
Journal / Book Title: IEEE/ACM Transactions on Audio, Speech and Language Processing
Volume: 26
Issue: 10
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/M026698/1
Copyright Statement: © 2018 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.
Publication Status: Published
Online Publication Date: 2018-06-08
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering



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