SPEECH DEREVERBERATION USINGWEIGHTED PREDICTION ERRORWITH LAPLACIAN MODEL OF THE DESIRED SIGNAL

Reverberation has a considerable impact on the quality and intel-ligibility of captured speech signals. In this paper we present an approach for blind multi-microphone speech dereverberation based on the weighted prediction error method, where the reverberant ob-servations are modeled using multi-channel linear prediction in the short-time Fourier transform domain. Instead of using the commonly employed Gaussian distribution for the desired speech signal, the proposed approach uses a Laplacian distribution which is known to be more accurate in modeling speech signals. Maximum-likelihood estimation is used for estimating the model parameters, leading to a linear programming optimization problem. Experimental results, obtained using measured impulse responses, indicate that the pro-posed approach could be used to improve the dereverberation per-formance compared to the classical technique. Index Terms — Dereverberation, speech enhancement, model-based signal processin