Improvement of independent vector analysis for closely spaced sources

Abstract

Independent vector analysis (IVA) is one of the most widely-used blind source separation methods. Theoretically, its performance is not affected by the location of the sound source, however, in practical applications with the presence of diffuse noise, the separation performance severely degrades when sources are closely spaced. In this technical note, the reason for this deterioration is explored and an effective modification of IVA cost function is proposed to compensate for the separation performance in closely-spaced source scenarios. Numerous experiments validate the effectiveness of the proposed method with its application to auxiliary function-based IVA.