GSVD-based optimal filtering for single and multimicrophone speech enhancement

By Simon Doclo, Marc Moonen. IEEE Transactions on Signal Processing, 2002

391 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computational Mechanics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/ff2b383dbc7a7630239fa13f5845410fa8ab056c

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In Biomedical Engineering

In Computational Mechanics

In Signal Processing

Citations in the corpus

New insights into the noise reduction Wiener filter (2006, background): “One of the first papers to do so is a paper written by Doclo and Moonen [13], where the optimal filter is derived as well as a general class of estimators.”
A Consolidated Perspective on Multimicrophone Speech Enhancement and Source Separation (2017, positive): “Using generalized singular value decomposition (GSVD), the mixture and noise covariance matrices can be jointly diagonalized [155].”
All-at-once Optimization for Coupled Matrix and Tensor Factorizations (2011, background): “, population differentiation in biology [31], blind source separation [37], multimicrophone speech filtering [11], and microarray data analysis [4, 5, 6].”
Multichannel Eigenspace Beamforming in a Reverberant Noisy Environment With Multiple Interfering Speech Signals (2009, methodology): “In [13], a multichannel Wiener filter (MWF) technique was proposed.”
On Optimal Frequency-Domain Multichannel Linear Filtering for Noise Reduction (2010, methodology): “In this context, several attempts have been made to enhance speech signals by not only denoising (i.e., removal of additive noise) but also dereverberating (i.e., removal of multiplicative noise) them using microphone arrays [9]–[11].”
On the Importance of the Pearson Correlation Coefficient in Noise Reduction (2008, background): “Let us choose , we have SNR (37) (38) (39) From this filter, we can deduce another interesting property of the SPCC. Property 10: We have SNR SNR (40) Since SNR SNR SNR, this implies that (41) which means that the filter yields less distortion to the clean speech signal than to the noise signal .”
Online detection and sorting of extracellularly recorded action potentials in human medial temporal lobe recordings, in vivo. (2006, methodology): “There exist methods for prewhitening of signals with rank-deficient noise (Doclo and Moonen 2002; Hansen 1998), but this is beyond the scope of this paper.”