Letters: Variational Bayesian method for speech enhancement

Authors:
Qinghua Huang;Jie Yang;Yue Zhou
Affiliations:
Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai 200240, China;Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai 200240, China;Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai 200240, China
Venue:
Neurocomputing
Year:
2007

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Abstract

In this paper, we propose to use variational Bayesian (VB) method to learn the clean speech signal from noisy observation directly. It models the probability distribution of clean signal using a Gaussian mixture model (GMM) and minimizes the misfit between the true probability distributions of hidden variables and model parameters and their approximate distributions. Experimental results demonstrate that the performance of the proposed algorithm is better than that of some other methods.