Joint blind dereverberation and separation of speech mixtures

Abstract

This paper proposes a method for jointly performing blind source separation (BSS) and blind dereverberation (BD) for speech mixtures. In most of the previous studies, BSS and BD have been explored separately. It is common that the performance of the speech separation algorithms deteriorates with the increase of room reverberations. Also most of the dereverberation algorithms rely on the availability of room impulse responses (RIRs) which are not readily accessible in practice. Therefore in this work the dereverberation and separation method are combined to mitigate the effects of room reverberations on the speech mixtures and hence to improve the separation performance. As required by the dereverberation algorithm, a step for blind estimation of reverberation time (RT) is used to estimate the decay rate of reverberations directly from the reverberant speech signal (i.e., speech mixtures) by modeling the decay as a Laplacian random process modulated by a deterministic envelope. Hence the developed algorithm works in a blind manner, i.e., directly dealing with the reverberant speech signals without explicit information from the RIRs. Evaluation results in terms of signal to distortion ratio (SDR) and segmental signal to reverberation ratio (SegSRR) reveal that using this method the performance of the separation algorithm that we have developed previously can be further enhanced.