In this paper, an extension of independent vector analysis (IVA), model-based IVA, is proposed for multichannel source separation. For obtaining better source models, we introduce a single-channel source separation method, and utilize the outputs as source variances in time-frequency-variant Gaussian source model. The demixing matrices are estimated in the same way as a state-of-the-art IVA method, auxiliary-function-based IVA (AuxIVA). Experimental evaluations show that the proposed approach is effective and improves the source separation performance of IVA. In addition, several post-filters aiming to realize multichannel Wiener filter (MWF) are investigated. This setup proves to further increase the performance of IVA. The presented method shows a potential to provide a general way to improve the separation performance from single-channel source separation to multichannel source separation.
|Title of host publication||IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia, April 19-24, 2015|
|Place of Publication||unknown|
|Publication status||Published - 2015|
|MoE publication type||A4 Article in a conference publication|
|Name||International Conference on Acoustics Speech and Signal Processing ICASSP|