Generalization of Multi-Channel Linear Prediction Methods for Blind MIMO Impulse Response Shortening

Abstract

The performance of many microphone array processing techniques deteriorates in the presence of reverberation. To provide a widely applicable solution to this longstanding problem, this paper generalizes existing dereverberation methods using subband-domain multi-channel linear prediction filters so that the resultant generalized algorithm can blindly shorten a multiple-input multiple-output (MIMO) room impulse response between a set of unknown number of sources and a microphone array. Unlike existing dereverberation methods, the presented algorithm is developed without assuming specific acoustic conditions, and provides a firm theoretical underpinning for the applicability of the subband-domain multi-channel linear prediction methods. The generalization is achieved by using a new cost function for estimating the prediction filter and an efficient optimization algorithm. The proposed generalized algorithm makes it easier to understand the common background underlying different dereverberation methods and future technical development. Indeed, this paper also derives two alternative dereverberation methods from the proposed algorithm, which are advantageous in terms of computational complexity. Experimental results are reported, showing that the proposed generalized algorithm effectively achieves blind MIMO impulse response shortening especially in a mid-to-high frequency range.