We introduce independent vector analysis (IVA) which is an extension of independent component analysis (ICA)
to multivariate components. In a set of ICA mixtures, IVA groups dependent source components across different
ICA mixtures and regard them as a multivariate source. This new formulation is an efficient framework for
solving the permutation problem in frequency-domain blind source separation (BSS) and its application to n×n
speech separation problem has been very successful. In this paper, we present a short tutorial on IVA and
summarize the various models that have been proposed to model the frequency components of speech.
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