Weighted Log-spectral Amplitude Estimation with Generalized Gamma Distribution under Speech Presence Probability

In this paper, we propose a speech enhancement approach. The approach is based on deriving weighted log-spectral amplitude estimator that exploits the generalized Gamma distributed speech priors under speech presence probability. The log-spectral amplitude estimator is weighted by psychoacoustically motivated speech distortion measure to take advantage of the perceptual interpretation. The experimental results show that the proposed approach provides less residual noise and better speech quality compared to stateof-the-art speech enhancement approaches.