ISCA Archive Interspeech 2008
ISCA Archive Interspeech 2008

Subspace based speech enhancement using Gaussian mixture model

Achintya Kundu, Saikat Chatterjee, T. V. Sreenivas

Traditional subspace based speech enhancement (SSE) methods use linear minimum mean square error (LMMSE) estimation that is optimal if the Karhunen Loeve transform (KLT) coefficients of speech and noise are Gaussian distributed. In this paper, we investigate the use of Gaussian mixture (GM) density for modeling the non-Gaussian statistics of the clean speech KLT coefficients. Using Gaussian mixture model (GMM), the optimum minimum mean square error (MMSE) estimator is found to be nonlinear and the traditional LMMSE estimator is shown to be a special case. Experimental results show that the proposed method provides better enhancement performance than the traditional subspace based methods.

doi: 10.21437/Interspeech.2008-45

Cite as: Kundu, A., Chatterjee, S., Sreenivas, T.V. (2008) Subspace based speech enhancement using Gaussian mixture model. Proc. Interspeech 2008, 395-398, doi: 10.21437/Interspeech.2008-45

  author={Achintya Kundu and Saikat Chatterjee and T. V. Sreenivas},
  title={{Subspace based speech enhancement using Gaussian mixture model}},
  booktitle={Proc. Interspeech 2008},