Subspace methods for multi-microphone speech dereverberation

S. Gannot, Marc Moonen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A novel approach for multimicrophone speech dereverberation is presented. The method is based on the construction of the null subspace of the data matrix in the presence of colored noise, using the generalized singular-value decomposition (GSVD) technique, or the generalized eigenvalue decomposition (GEVD) of the respective correlation matrices. The special Silvester structure of the filtering matrix, related to this subspace, is exploited for deriving a total least squares (TLS) estimate for the acoustical transfer functions (ATFs). Other less robust but computationally more efficient methods are derived based on the same structure and on the QR decomposition (QRD). A preliminary study of the incorporation of the subspace method into a subband framework proves to be efficient, although some problems remain open. Speech reconstruction is achieved by virtue of the matched filter beamformer (MFBF). An experimental study supports the potential of the proposed methods.
Original languageAmerican English
Title of host publicationThe International Workshop on Acoustic Echo and Noise Control (IWAENC)
PublisherEURASIP Journal on Applied Signal Processing
StatePublished - 2003

Bibliographical note

Place of conference:Darmstadt, Germany

Fingerprint

Dive into the research topics of 'Subspace methods for multi-microphone speech dereverberation'. Together they form a unique fingerprint.

Cite this