  Independent Vector Analysis (IVA) is a popular extension of Independent
Component Analysis (ICA) for joint separation of a set of instantaneous linear
mixtures, with a direct application in frequency-domain speaker separation or
extraction. The mixtures are parameterized by mixing matrices, one matrix per
mixture. This means that the IVA mixing model does not account for any
relationships between parameters across the mixtures/frequencies. The
separation proceeds jointly only through the source model, where statistical
dependencies of sources across the mixtures are taken into account. In this
paper, we propose a mixing model for joint blind source extraction where the
mixing model parameters are linked across the frequencies. This is achieved by
constraining the set of feasible parameters to the manifold of half-length
separating filters, which has a clear interpretation and application in
frequency-domain speaker extraction.
