Speech Enhancement Using MMSE Estimator Based on Mixture of Laplacian

In this paper an statistical speech enhancement method based on Laplacian Mixture Model assumption for speech in order to estimation of clean speech from noisy speech has been proposed. In the proposed method, the short time discrete Fourier transform coefficients (DFT) have been estimated by using the minimum mean square error estimator. We assume the mixture of Laplacians distribution for clean speech DFT coefficients and zero-mean Gaussian distribution for the DFT coefficients of noise. The results of segmental SNR, LLR and PESQ show that the proposed method has better performance than two estimators based on Gaussian and Laplacin model.