@inproceedings{9e78838253864b24a8669b24f16f947f,
title = "Designing multichannel source separation based on single-channel source separation",
abstract = "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.",
author = "{Ramirez Lopez}, Ana and Nobutaka Ono and Ulpu Remes and Kalle Palom{\"a}ki and Mikko Kurimo",
note = "VK: COIN",
year = "2015",
language = "English",
isbn = "978-1-4673-6997-8",
series = "International Conference on Acoustics Speech and Signal Processing ICASSP",
publisher = "IEEE",
pages = "469--473",
booktitle = "IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia, April 19-24, 2015",
address = "United States",
}