Blind speech dereverberation with multi-channel linear prediction based on short time fourier transform representation

Abstract

It has recently been shown that the use of the time-varying nature of speech signals allows us to achieve high quality speech dereverberation based on multi-channel linear prediction (MCLP). However, this approach requires a huge computing cost for calculating large covariance matrices in the time domain. In addition, we face the important problem of how to combine the speech dereverberation efficiently with many other useful speech enhancement techniques in the short time Fourier transform (STFT) domain. As the first step to overcoming these problems, this paper presents methods for implementing MCLP based speech dereverberation that allow it to work in the STFT domain with much less computing cost. The effectiveness of the present methods is confirmed by experiments in terms of the recovered signal quality and the computing time.