I-Divergence-based dereverberation method with auxiliary function approach

Abstract

This paper presents a dereverberation method based on I-divergence minimization, which is particularly suitable for music signals. Existing dereverberation methods, including one designed for music, sometimes distort instrument sounds and make staccato-like tones. The problems with the Itakura-Saito-divergence-based formulation of the existing methods are 1) their tendency to excessive suppression of direct sound and 2) the difficulty of incorporating and optimizing sophisticated source models suitable for music signals. The proposed I-divergence-based method can mitigate these problems. Employing the I-divergence measure enables us to avoid the direct sound suppression problem and to use powerful music spectrum models without complicating its optimization. We develop a convergence-guaranteed parameter estimation algorithm based on the auxiliary function approach. Experimental results reveal the effectiveness of the proposed dereverberation method.