T. Higuchi, N. Takamune, N. Tomohiko, and H. Kameoka, Underdetermined blind separation and tracking of moving sources based on DOA-HMM, IEEE ICASSP, 2014.

T. Higuchi and H. Kameoka, Unified approach for audio source separation with multichannel factorial HMM and DOA mixture model, 2015 23rd European Signal Processing Conference (EUSIPCO), 2015.
DOI : 10.1109/EUSIPCO.2015.7362743
URL : https://zenodo.org/record/38902

L. Parra and C. Spence, Convolutive blind separation of non-stationary sources, IEEE Transactions on Speech and Audio Processing, vol.8, issue.3, pp.320-327, 2000.
DOI : 10.1109/89.841214

F. Neeser, J. Massey, D. Kounades-bastian, L. Girin, X. Alameda-pineda et al., Proper complex random processes with applications to information theory A variational EM algorithm for the separation of time-varying convolutive audio mixtures, IEEE Trans. Info. Theory IEEE TASLP, vol.3914, issue.24 8, pp.1293-1302, 1993.

S. Arberet, A. Ozerov, N. Q. Duong, E. Vincent, R. Gribonval et al., Nonnegative matrix factorization and spatial covariance model for under-determined reverberant audio source separation, 10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010), 2010.
DOI : 10.1109/ISSPA.2010.5605570
URL : https://hal.archives-ouvertes.fr/inria-00541436

L. Benaroya, L. Donagh, F. Bimbot, and R. Gribonval, Non negative sparse representation for Wiener based source separation with a single sensor, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., pp.613-616, 2003.
DOI : 10.1109/ICASSP.2003.1201756
URL : https://hal.archives-ouvertes.fr/inria-00574784

C. Févotte, N. Bertin, and J. Durrieu, Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis, Neural Computation, vol.14, issue.3, pp.793-830, 2009.
DOI : 10.1016/j.sigpro.2007.01.024

N. Mohammadiha, P. Smaragdis, and A. Leijon, Supervised and Unsupervised Speech Enhancement Using Nonnegative Matrix Factorization, IEEE Transactions on Audio, Speech, and Language Processing, vol.21, issue.10, pp.2140-2151, 2013.
DOI : 10.1109/TASL.2013.2270369
URL : http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-124353

C. Bishop, Pattern Recognition and Machine Learning, 2006.

N. Sturmel, A. Liutkus, J. Pinel, L. Girin, S. Marchand et al., Linear mixing models for active listening of music productions in realistic studio conditions, Proc. Audio Eng. Soc, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00790783

J. S. Garofolo, L. F. Lamel, W. M. Fisher, J. G. Fiscus, D. S. Pallett et al., Timit acoustic-phonetic continuous speech corpus, linguistic Data Consortium, 1993.

C. Hummersone, R. Mason, and T. Brookes, A comparison of computational precedence models for source separation in reverberant environments, J. Audio Eng. Soc, vol.61, issue.78, pp.508-520, 2013.

E. Vincent, R. Gribonval, and C. Févotte, Performance measurement in blind audio source separation, IEEE Transactions on Audio, Speech and Language Processing, vol.14, issue.4, pp.1462-1469, 2006.
DOI : 10.1109/TSA.2005.858005
URL : https://hal.archives-ouvertes.fr/inria-00544230

G. J. Mysore, P. Smaragdis, and R. Bliksha, Nonnegative hidden markov modeling of audio with application to source separation, Proc. Int. Conf. on Latent Variable Analysis and Signal Separation, 2010.