Suppression of additive noise using a power spectral density MMSE estimator

In this letter, we propose a novel speech enhancement approach, called power spectral density minimum mean-square error (PSD-MMSE) estimation-based speech enhancement, which is implemented in the power spectral domain where stationary stochastic noise can be modeled as the exponential distribution. Speech magnitude-squared spectra are modeled as the mixed exponential distribution. And an MMSE estimator is constructed based on the parametric distributions. Besides, a fast algorithm is presented to implement the approach in real time. Experimental results of Itakura-Saito distortion measures show that the proposed approach is superior to alternative speech enhancement algorithms.