ARTICLE mccowan-rr-01-40b/IDIAP Microphone Array Post-filter based on Noise Field Coherence McCowan, Iain A. Bourlard, Hervé EXTERNAL http://publications.idiap.ch/attachments/reports/2001/rr01-40.pdf PUBLIC http://publications.idiap.ch/index.php/publications/showcite/mccowan-rr-01-40 Related documents IEEE Transactions on Speech and Audio Processing 11 6 709-716 2003 November 2003 IDIAP-RR 01-40 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. REPORT mccowan-rr-01-40/IDIAP Microphone Array Post-filter based on Noise Field Coherence McCowan, Iain A. Bourlard, Hervé EXTERNAL http://publications.idiap.ch/attachments/reports/2001/rr01-40.pdf PUBLIC Idiap-RR-40-2001 2001 IDIAP Martigny, Switzerland Published in IEEE Transactions on Speech and Audio Processing, pp 709-716, Vol 11, No 6, November 2003 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.