Generalized gamma modeling of speech and its online estimation for speech enhancement

Generalized gamma modeling and its online method of parameter estimation of speech spectral magnitude are proposed for MAP based speech enhancement systems. Generalized gamma modeling is shown to be a natural extension of the Gaussian modeling of speech spectral component distribution, and is therefore, able to fit the prior distribution better than the conventional method. An online parameter estimation method for the gamma distribution, based on a moment matching method, is then proposed. The effectiveness of the proposed methods are confirmed by improvement in both SNR and ASR using the AURORA2 standard database, where about 4 dB improvement in SNR and 20% improvement in relative ASR performance are obtained.