GMM based Bayesian approach to speech enhancement in signal / transform domain

@article{Kundu2008GMMBB,
  title={GMM based Bayesian approach to speech enhancement in signal / transform domain},
  author={Achintya Kundu and Saikat Chatterjee and A. Sreenivasa Murthy and Thippur V. Sreenivas},
  journal={2008 IEEE International Conference on Acoustics, Speech and Signal Processing},
  year={2008},
  pages={4893-4896}
}
Considering a general linear model of signal degradation, by modeling the probability density function (PDF) of the clean signal using a Gaussian mixture model (QMM) 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… CONTINUE READING
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