Combination of sparsity of direct waves and detection of signal for distant speech enhancement

Abstract

A joint dereverberation and denoising framework is proposed for enhancement of distant speech in a conference room. The sparsity of speech multipath propagation is exploited by a microphone array for suppressing late reverberation. The dereverberation speech is transformed to solve a minimization problem where the sparse prediction coefficients are estimated by a least-square iteration algorithm. The residual noise components are removed by iteratively reconstructing the time–frequency spectrum of speech signals. Detection of speech presence is carried out over each cell of the spectrum based on the Bayes rule. The data analysis and the real-time processing results have shown that the proposed joint framework outperforms the existing approaches in terms of objective metrics of speech quality.