Frequency-domain beamformers using conjugate gradient techniques for speech enhancement

Zhao,S, Jones,DL, Khoo,S and Man,Z 2014, Frequency-domain beamformers using conjugate gradient techniques for speech enhancement, Journal of the Acoustical Society of America, vol. 136, no. 3, pp. 1160-1175, doi: 10.1121/1.4892780.

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Title Frequency-domain beamformers using conjugate gradient techniques for speech enhancement
Author(s) Zhao,S
Journal name Journal of the Acoustical Society of America
Volume number 136
Issue number 3
Start page 1160
End page 1175
Total pages 16
Publisher Acoustical Society of America
Place of publication New York, N.Y.
Publication date 2014
ISSN 0001-4966
Keyword(s) Science & Technology
Life Sciences & Biomedicine
Audiology & Speech-Language Pathology
Summary A multiple-iteration constrained conjugate gradient (MICCG) algorithm and a single-iteration constrained conjugate gradient (SICCG) algorithm are proposed to realize the widely used frequency-domain minimum-variance-distortionless-response (MVDR) beamformers and the resulting algorithms are applied to speech enhancement. The algorithms are derived based on the Lagrange method and the conjugate gradient techniques. The implementations of the algorithms avoid any form of explicit or implicit autocorrelation matrix inversion. Theoretical analysis establishes formal convergence of the algorithms. Specifically, the MICCG algorithm is developed based on a block adaptation approach and it generates a finite sequence of estimates that converge to the MVDR solution. For limited data records, the estimates of the MICCG algorithm are better than the conventional estimators and equivalent to the auxiliary vector algorithms. The SICCG algorithm is developed based on a continuous adaptation approach with a sample-by-sample updating procedure and the estimates asymptotically converge to the MVDR solution. An illustrative example using synthetic data from a uniform linear array is studied and an evaluation on real data recorded by an acoustic vector sensor array is demonstrated. Performance of the MICCG algorithm and the SICCG algorithm are compared with the state-of-the-art approaches.
Language eng
DOI 10.1121/1.4892780
Field of Research 090609 Signal Processing
090601 Circuits and Systems
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, Acoustical Society of America
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Document type: Journal Article
Collection: School of Engineering
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