Kundu, Achintya and Chatterjee, Saikat and Murthy, Sreenivasa A and Sreenivas, TV (2008) GMM basedbayesian approach to speech enhancement in signal/transform domain. In: Proceedings IEEE Int. Conf. Acoust. Speech and Signal Proc.,, March 31 2008-April 4 2008 , Las Vegas, NV .
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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|
|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.|
|Keywords:||MMSE estimation;GMM;Gaussian noise.|
|Department/Centre:||Division of Electrical Sciences > Electrical Communication Engineering|
|Date Deposited:||20 Sep 2011 07:14|
|Last Modified:||20 Sep 2011 07:14|
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