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.