  Independent Vector Analysis (IVA) is an effective approach for Blind Source
Separation (BSS) of convolutive mixtures of audio signals. As a practical
realization of an IVA-based BSS algorithm, the so-called AuxIVA update rules
based on the Majorize-Minimize (MM) principle have been proposed which allow
for fast and computationally efficient optimization of the IVA cost function.
For many real-time applications, however, update rules for IVA exhibiting even
faster convergence are highly desirable. To this end, we investigate techniques
which accelerate the convergence of the AuxIVA update rules without extra
computational cost. The efficacy of the proposed methods is verified in
experiments representing real-world acoustic scenarios.
