Iterative cepstrum-based approach for speech dereverberation

This paper presents a novel approach for dereverberation of speech signals, based on an iterative cepstral separation of the non-minimum phase room response. The algorithm performs an iterative flattening of the room transfer function (RTF) magnitude spectrum prior to suppression of phase distortion. For ill-conditioned inversion problems, the proposed method is superior to the standard homomorphic techniques, as it overcomes the loss in computational efficiency inflicted by the long time responses of the inverse filters. By using the fast-decaying sequences shorter than the length of a full inverse, the finite-point nature of a discrete Fourier transform (DFT) is made noncritical. Results with measured room responses conform with the theory presented in the paper.