Multichannel speech dereverberation and separation with optimized combination of linear and non-linear filtering

In this paper, we propose a multichannel speech dereverberation and separation technique which is effective even when there are multiple speakers and each speaker's transfer function is time-varying due to fluctuation of the corresponding speaker's head. For robustness against fluctuation, the proposed method optimizes linear filtering with non-linear filtering simultaneously from probabilistic perspective based on a probabilistic reverberant transfer-function model, PRTFM. PRTFM is an extension of the conventional time-invariant transfer-function model under uncertain conditions, and PRTFM can be also regarded as an extension of recently proposed blind local Gaussian modeling. The linear filtering and the non-linear filtering are optimized in MMSE (Minimum Mean Square Error) sense during parameter optimization. The proposed method is evaluated in a reverberant meeting room, and the proposed method is shown to be effective.