%Aigaion2 BibTeX export from Idiap Publications
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@TECHREPORT{mccowan-rr-01-40,
                      author = {McCowan, Iain A. and Bourlard, Herv{\'{e}}},
                    projects = {Idiap},
                       title = {Microphone Array Post-filter based on Noise Field Coherence},
                        type = {Idiap-RR},
                      number = {Idiap-RR-40-2001},
                        year = {2001},
                 institution = {IDIAP},
                     address = {Martigny, Switzerland},
                        note = {Published in IEEE Transactions on Speech and Audio Processing, pp 709-716, Vol 11, No 6, November 2003},
                    abstract = {This article introduces a novel technique for estimating the signal power spectral density to be used in the transfer function of a microphone array post-filter. The technique is a generalisation of the existing Zelinski post-filter, which uses the auto- and cross-spectral densities of the array inputs to estimate the signal and noise spectral densities. The Zelinski technique, however, assumes zero cross-correlation between the noise on different sensors. This assumption is inaccurate, particularly at low frequencies and for arrays with closely spaced sensors, and thus the corresponding post-filter is sub-optimal in realistic noise conditions. In this article, a more general expression of the post-filter estimation is developed based on an assumed knowledge of the complex coherence of the noise field. This general expression can be used to construct a more appropriate post-filter in a variety of different noise fields. In experiments using real noise recordings from a computer office, the modified post-filter results in significant improvement in terms of objective speech quality measures and speech recognition performance using a diffuse noise model.},
                         pdf = {https://publications.idiap.ch/attachments/reports/2001/rr01-40.pdf},
                  postscript = {ftp://ftp.idiap.ch/pub/reports/2001/rr01-40.ps.gz},
ipdinar={2001},
ipdmembership={speech},
language={English},
}