Speech dereverberation using weighted prediction error with correlated inter-frame speech components

In this paper, we propose a new dereverberation approach based on the weighted prediction error (WPE) method implemented in the short-time Fourier transform (STFT) domain. Our main contribution is to model the temporal correlation of the STFT coefficients across analysis frames, referred to as inter-frame correlation (IFC), and exploit it in the dereverberation process. Since accurate modeling of the IFC is not tractable, we consider an approximate model wherein only a finite number of consecutive speech frames are considered correlated. It is shown that, given an estimate of the IFC matrix, the proposed approach results in a convex quadratic optimization problem with respect to the reverberation prediction weights, and a closed-form solution can be accordingly derived. Furthermore, an efficient method for the estimation of the underlying IFC matrix is developed based on the extension of a recently proposed speech variance estimator. We evaluate the performance of our approach incorporating the estimated IFC matrix and compare it to the original and several variants of the WPE method. The results reveal lower residual reverberation and higher overall quality of the enhanced speech when the proposed method is employed.