MMSE Log-Spectral Amplitude Estimation Under Speech Presence Uncertainty Using Generalized Gamma Speech Priors

MMSE log-spectral amplitude (LSA) estimators offer convincing performance and are, therefore, widely spread in speech enhancement. In this paper an MMSE-LSA estimation under speech presence uncertainty (SPU) with a generalized gamma speech prior representing a variety of speech priors is proposed. Employing a gamma speech prior as a special case of the generalized approach, a numerical approximation is employed. Different to most state-of-the-art approaches, we choose the pdf assumptions of the mere spectral weighting rule and of the SPU estimation to be consistent. It is shown that the use of the SPU estimator with an underlying gamma speech pdf yields more than a 3 dB gain in noise attenuation, with a slight advantage versus the Gaussian SPU estimator.