GMM based Bayesian approach to speech enhancement in signal transform domain

Kundu, Achintya and Chatterjee, Saikat and Murthy, A Sreenivasa and Sreenivas, TV (2008) GMM based Bayesian approach to speech enhancement in signal transform domain. In: 33rd IEEE International Conference on Acoustics, Speech and Signal Processing, MAR 30-APR 04, 2008, Las Vegas.

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Abstract

Considering a general linear model of signal degradation, by modeling the probability density function (PDF) of the clean signal using a Gaussian mixture model (GMM) and additive noise by a Gaussian PDF, we derive the minimum mean square error (MMSE) estimator. The derived MMSE estimator is non-linear and the linear MMSE estimator is shown to be a special case. For speech signal corrupted by independent additive noise, by modeling the joint PDF of time-domain speech samples of a speech frame using a GMM, we propose a speech enhancement method based on the derived MMSE estimator. We also show that the same estimator can be used for transform-domain speech enhancement.

Item Type:	Conference Paper
Publisher:	IEEE
Additional Information:	Copyright 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	23 Mar 2010 11:36
Last Modified:	19 Sep 2010 05:58
URI:	http://eprints.iisc.ac.in/id/eprint/26473

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