Speech enhancement using MMSE short time spectral estimation with gamma distributed speech priors

In this paper we consider optimal estimators for speech enhancement in the Discrete Fourier Transform (DFT) domain. We present an analytical solution for estimating complex DFT coefficients in the MMSE sense when the clean speech DFT coefficients are Gamma distributed and the DFT coefficients of the noise are Gaussian or Laplace distributed. Compared to the state-of-the-art Wiener or MMSE short time amplitude estimators the new estimators deliver improved signal-to-noise ratios. When the noise model is a Laplacian density the enhanced speech shows less annoying random fluctuations in the residual noise than for a Gaussian density.