A numerical approach for estimating optimal gain functions in single-channel dft based speech enhancement

We treat the problem of finding minimum mean-square error (MMSE) spectral amplitude estimators for discrete Fourier transform (DFT) based single-channel noise suppression al-gorithms. Existing schemes derive gain functions analyt-ically based on distributional assumptions with respect to the speech (and noise) DFT coefficients and on mathemat-ically tractable distortion measures. In this paper we pro-pose a methodology to estimate the MMSE gain functions directly from speech signals, without assuming that speech DFT coefficients follow a certain parametrized probability density function. Furthermore, the proposed scheme allows for estimation of MMSE gain functions for pdf/distortion measure combinations for which no analytical solutions are known. Simulation experiments where noisy speech is en-hanced using the estimated gain functions show promising results. Specifically, the estimated gain functions perform better than standard schemes, as measured by a range of ob-jective speech quality criteria. 1