E. Cherry, Some Experiments on the Recognition of Speech, with One and with Two Ears, The Journal of the Acoustical Society of America, vol.25, issue.5, pp.975-979, 1953.
DOI : 10.1121/1.1907229

E. Cherry and W. Taylor, Some Further Experiments upon the Recognition of Speech, with One and with Two Ears, The Journal of the Acoustical Society of America, vol.26, issue.4, pp.554-559, 1954.
DOI : 10.1121/1.1907373

S. Haykin and Z. Chen, The Cocktail Party Problem, Neural Computation, vol.31, issue.2, pp.1875-1902, 2005.
DOI : 10.1016/0378-5955(91)90148-3

J. H. Mcdermott, The cocktail party problem, Current Biology, vol.19, issue.22, pp.1024-1027, 2009.
DOI : 10.1016/j.cub.2009.09.005

H. Mcgurk and J. Macdonald, Hearing lips and seeing voices, Nature, vol.65, issue.5588, 1976.
DOI : 10.1044/jshr.1704.619

E. M. Golumbic, N. Ding, S. Bickel, P. Lakatos, C. A. Schevon et al., Mechanisms underlying selective neuronal tracking of attended speech at a cocktail party, Neuron, vol.77, issue.5, pp.980-991, 2013.

A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis, actions on Audio, Speech, and Language Processing, pp.382-394, 2001.

A. Cichocki, R. Zdunek, A. H. Phan, and S. Amari, Nonnegative matrix and tensor factorizations: Applications to exploratory multi-way data analysis and blind source separation, 2009.
DOI : 10.1002/9780470747278

A. Simpson, G. Roma, and M. D. Plumbley, Deep Karaoke: Extracting Vocals from Musical Mixtures Using a Convolutional Deep Neural Network, 2015.
DOI : 10.1007/978-3-319-22482-4_50

B. Rivet, W. Wang, S. Naqvi, and J. Chambers, Audiovisual Speech Source Separation: An overview of key methodologies, IEEE Signal Processing Magazine, vol.31, issue.3, pp.125-134, 2014.
DOI : 10.1109/MSP.2013.2296173
URL : https://hal.archives-ouvertes.fr/hal-00990000

A. Cichocki and S. Amari, Adaptive blind signal and image processing: Learning algorithms and applications, 2002.
DOI : 10.1002/0470845899

J. Hérault and C. Jutten, Space or time adaptive signal processing by neural network models, AIP Conference Proceedings, pp.206-211, 1986.
DOI : 10.1063/1.36258

A. J. Bell and T. J. Sejnowski, An Information-Maximization Approach to Blind Separation and Blind Deconvolution, Neural Computation, vol.20, issue.1, pp.1129-1159, 1995.
DOI : 10.1109/78.301850
URL : http://bme.iust.ac.ir/courses/adsp/adsp_ref16.pdf

T. Lee, M. Girolami, and T. J. Sejnowski, Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources, Neural Computation, vol.28, issue.46
DOI : 10.1109/72.536322
URL : http://papers.cnl.salk.edu/PDFs/Independent%20Component%20Analysis%20Using%20an%20Extended%20Infomax%20Algorithm%20for%20Mixed%20Subgaussian%20and%20Supergaussian%20Sources%201999-3779.pdf

E. Bingham and A. Hyvärinen, A FAST FIXED-POINT ALGORITHM FOR INDEPENDENT COMPONENT ANALYSIS OF COMPLEX VALUED SIGNALS, International Journal of Neural Systems, vol.10, issue.01, pp.1-8, 2000.
DOI : 10.1016/S0165-1684(97)00197-7

J. Cardoso and A. Souloumiac, Blind beamforming for non-gaussian signals, IEE Proceedings on Radar and Signal Processing, pp.362-370, 1993.
DOI : 10.1049/ip-f-2.1993.0054

A. Hyvärinen, Independent component analysis: recent advances, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.14, issue.3, pp.20-110, 1984.
DOI : 10.1109/TNN.2003.810616

M. S. Pedersen, J. Larsen, U. Kjems, and L. C. Parra, A survey of convolutive blind source separation methods, Multichannel Speech Processing Handbook, pp.1065-1084, 2007.

M. Davies, Audio source separation, " in Institute of Mathematics and its applications conference series, pp.57-68, 2002.

P. Smaragdis, Efficient blind separation of convolved sound mixtures, Proceedings of 1997 Workshop on Applications of Signal Processing to Audio and Acoustics, p.4, 1997.
DOI : 10.1109/ASPAA.1997.625609

F. Duplessis-beaulieu and B. Champagne, Fast convolutive blind speech separation via subband adaptation, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., p.513, 2003.
DOI : 10.1109/ICASSP.2003.1200019
URL : http://digitool.Library.McGill.CA:80/webclient/DeliveryManager?pid=29535&custom_att_2=direct

P. Smaragdis, Blind separation of convolved mixtures in the frequency domain, Neurocomputing, vol.22, issue.1-3, pp.21-34, 1998.
DOI : 10.1016/S0925-2312(98)00047-2

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

S. Naqvi, M. Yu, and J. Chambers, A Multimodal Approach to Blind Source Separation of Moving Sources, IEEE Journal of Selected Topics in Signal Processing, vol.4, issue.5, pp.895-910, 2010.
DOI : 10.1109/JSTSP.2010.2057198

D. Yellin and E. Weinstein, Criteria for multichannel signal separation, IEEE Transactions on Signal Processing, vol.42, issue.8, pp.2158-2168, 1994.
DOI : 10.1109/78.301850

S. Makino, T. Lee, and H. Sawada, Blind speech separation, 2007.
DOI : 10.1007/978-1-4020-6479-1

T. Kim, H. T. Attias, S. Lee, and T. Lee, Blind Source Separation Exploiting Higher-Order Frequency Dependencies, IEEE Transactions on Audio, Speech and Language Processing, vol.15, issue.1, pp.70-79, 2007.
DOI : 10.1109/TASL.2006.872618

T. Adali, M. Anderson, and F. Geng-shen, Diversity in Independent Component and Vector Analyses: Identifiability, algorithms, and applications in medical imaging, IEEE Signal Processing Magazine, vol.31, issue.3, pp.18-33, 2014.
DOI : 10.1109/MSP.2014.2300511

M. Joho, H. Mathis, and R. H. Lambert, Overdetermined blind source separation: Using more sensors than source signals in a noisy mixture, Proceedings of ICA, pp.81-86, 2000.

S. Amari, Natural Gradient Works Efficiently in Learning, Neural Computation, vol.37, issue.2, pp.251-276, 1998.
DOI : 10.1103/PhysRevLett.76.2188

H. N. Thi and C. Jutten, Blind source separation for convolutive mixtures, Signal Processing, vol.45, issue.2, pp.209-229, 1995.
DOI : 10.1016/0165-1684(95)00052-F

J. Xi and J. Reilly, Blind separation and restoration of signals mixed in convolutive environment, IEEE International Conference on Acoustics, Speech, and Signal Processing, p.1327, 1997.

K. Torkkola, Blind separation of convolved sources based on information maximization, Neural Networks for Signal Processing VI. Proceedings of the 1996 IEEE Signal Processing Society Workshop, pp.423-432, 1996.
DOI : 10.1109/NNSP.1996.548372

H. Sawada, R. Mukai, S. Araki, and S. Makino, A Robust and Precise Method for Solving the Permutation Problem of Frequency-Domain Blind Source Separation, IEEE Transactions on Speech and Audio Processing, vol.12, issue.5, pp.530-538, 2004.
DOI : 10.1109/TSA.2004.832994

J. Cardoso, Multidimensional independent component analysis, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181), pp.1941-1944, 1998.
DOI : 10.1109/ICASSP.1998.681443
URL : http://www.tsi.enst.fr/~cardoso/Papers.PS/icassp98.ps

A. Hyvärinen and U. Köster, FastISA: A fast fixed-point algorithm for independent subspace analysis, 14th European Symposium on Artificial Neural Networks, pp.371-376, 2006.

I. Lee, T. Kim, and T. Lee, Independent Vector Analysis for Convolutive Blind Speech Separation, Blind speech separation, pp.169-192, 2007.
DOI : 10.1007/978-1-4020-6479-1_6

N. Ono, Blind Source Separation On iPhone In Real Enviroment, 2013 European Signal Processing Conference, p.2013

I. Lee, T. Kim, and T. Lee, Fast fixed-point independent vector analysis algorithms for convolutive blind source separation, Signal Processing, vol.87, issue.8, pp.1859-1871, 2007.
DOI : 10.1016/j.sigpro.2007.01.010

M. R. Schroeder, New Method of Measuring Reverberation Time, The Journal of the Acoustical Society of America, vol.37, issue.3, pp.409-412, 1965.
DOI : 10.1121/1.1909343

C. Brown, Matlab central, t60.m, pp.10-16, 2002.

J. Allen, D. G. Berkley-]-b, N. Shinn-cunningham, T. Kopco, and . Martin, Image method for efficiently simulating small-room acoustics Journal of the Acoustic Society of [54 Localizing nearby sound sources in a classroom: Binaural room impulse responses, Journal of the Acoustic Society of America, vol.117, p.3100, 2005.

A. Lundeby, T. E. Vigran, H. Bietz, and M. Vorländer, Uncertainties of measurements in room acoustics, Acta Acustica united with Acustica, vol.81, issue.4, pp.344-355, 1995.

C. Févotte, R. Gribonval, and E. Vincent, BSS EVAL toolbox user guide, 2005.

W. Baumann, B. Kohler, D. Kolossa, and R. Orglmeister, Real time separation of convolutive mixtures, Proceedings of ICA 2001, pp.65-69, 2001.

B. Gunel, H. Hacihabiboglu, and A. M. Kondoz, Acoustic Source Separation of Convolutive Mixtures Based on Intensity Vector Statistics, IEEE Transactions on Audio, Speech, and Language Processing, vol.16, issue.4, pp.748-756, 2008.
DOI : 10.1109/TASL.2008.918967

I. Jolliffe, Principal component analysis, 2002.

S. Naqvi, Y. Zhang, and J. Chambers, Multimodal Blind Source Separation for Moving Sources, IEEE International Conference on Acoustics, Speech and Signal Processing, pp.125-128, 2009.
DOI : 10.1109/icassp.2009.4959536
URL : https://dspace.lboro.ac.uk/dspace-jspui/bitstream/2134/5352/1/naqvi.pdf

S. Naqvi, W. Wang, M. Khan, M. Barnard, and J. Chambers, Multimodal (audio???visual) source separation exploiting multi-speaker tracking, robust beamforming and time???frequency masking, IET Signal Processing, vol.6, issue.5, pp.466-477, 2012.
DOI : 10.1049/iet-spr.2011.0124

D. Gatica-perez, G. Lathoud, J. Odobez, and I. Mccowan, Audiovisual Probabilistic Tracking of Multiple Speakers in Meetings, IEEE Transactions on Audio, Speech and Language Processing, vol.15, issue.2, pp.601-616, 2007.
DOI : 10.1109/TASL.2006.881678

D. B. Ward, E. A. Lehmann, and R. C. Williamson, Particle filtering algorithms for tracking an acoustic source in a reverberant environment, IEEE Transactions on Speech and Audio Processing, vol.11, issue.6, pp.826-836, 2003.
DOI : 10.1109/TSA.2003.818112

I. Potamitis, H. Chen, and G. Tremoulis, Tracking of Multiple Moving Speakers With Multiple Microphone Arrays, IEEE Transactions on Speech and Audio Processing, vol.12, issue.5, pp.520-529, 2004.
DOI : 10.1109/TSA.2004.833004

B. Rivet, L. Girin, and C. Jutten, Visual voice activity detection as a help for speech source separation from convolutive mixtures, Speech Communication, vol.49, issue.7-8, pp.667-677, 2006.
DOI : 10.1016/j.specom.2007.04.008
URL : https://hal.archives-ouvertes.fr/hal-00499184

J. Harris, S. Naqvi, B. Rivet, J. Chambers, and C. Jutten, Visual based reference for enhanced audio-visual source extraction, 9th IMA International Conference on Mathematics
URL : https://hal.archives-ouvertes.fr/hal-00781793

M. Pedersen, J. Larsen, U. Kjems, and L. C. Parra, A survey of convolutive blind source separation methods, Multichannel Speech Processing Handbook, pp.1065-1084, 2007.

I. Cohen, Analysis of two-channel generalized sidelobe canceller (GSC) with post-filtering, IEEE Transactions on Speech and Audio Processing, vol.11, issue.6, pp.684-699, 2003.
DOI : 10.1109/TSA.2003.818105

L. J. Griffiths and C. W. Jim, An alternative approach to linearly constrained adaptive beamforming, IEEE Transactions on Antennas and Propagation, vol.30, issue.1, pp.27-34, 1982.
DOI : 10.1109/TAP.1982.1142739

B. Van-veen and K. Buckley, Beamforming: a versatile approach to spatial filtering, IEEE ASSP Magazine, vol.5, issue.2, pp.4-24, 1988.
DOI : 10.1109/53.665

S. Araki, R. Mukai, S. Makino, T. Nishikawa, and H. Saruwatari, The fundamental limitation of frequency domain blind source separation for convolutive mixtures of speech, IEEE Transactions on Speech and Audio Processing, vol.11, issue.2, pp.109-116, 2003.
DOI : 10.1109/TSA.2003.809193

N. Forsyth, J. Chambers, and P. Naylor, Alternating fixedpoint algorithm for stereophonic acoustic echo cancellation, IEE Proceedings on Vision, Image and Signal Processing, pp.1-9, 2002.
DOI : 10.1049/ip-vis:20020148

A. Björck and G. H. Golub, Numerical Methods for Computing Angles Between Linear Subspaces, Mathematics of Computation, vol.27, issue.123, pp.579-594, 1973.
DOI : 10.2307/2005662

C. Goodlin, Adaptive noise cancelling: Principles and applications, Proceedings of the IEEE, vol.63, issue.12, pp.1692-1716, 1975.

B. Widrow and S. D. Stearns, Adaptive signal processing, 1985.

S. Haykin, Adaptive Filter Theory, 2002.

T. Kim, Real-time independent vector analysis for convolutive blind source separation, IEEE Transactions on Circuits and Systems I: Regular Papers, vol.57, issue.7, pp.1431-1438, 2010.

J. Hao, I. Lee, T. Lee, and T. Sejnowski, Independent Vector Analysis for Source Separation Using a Mixture of Gaussians Prior, Neural Computation, vol.13, issue.6, pp.1646-1673, 2010.
DOI : 10.1016/S0925-2312(98)00047-2

T. Taniguchi, N. Ono, A. Kawamura, and S. Sagayama, An auxiliary-function approach to online independent vector analysis for real-time blind source separation, 2014 4th Joint Workshop on Hands-free Speech Communication and Microphone Arrays (HSCMA), pp.107-111, 2014.
DOI : 10.1109/HSCMA.2014.6843261

S. Ding, J. Huang, D. Wei, and A. Cichocki, A near real-time approach for convolutive blind source separation, IEEE Transactions on Circuits and Systems I: Regular Papers, vol.53, issue.1, pp.114-128, 2006.
DOI : 10.1109/TCSI.2005.854295

. Gomez-castaneda, DSP implementation of extended infomax ICA algorithm for blind source separation, 3rd International Conference on Electrical and Electronics Engineering, pp.1-4, 2006.

R. Mukai, H. Sawada, S. Araki, and S. Makino, Real-time blind source separation for moving speakers using blockwise ICA and residual crosstalk subtraction, Proceedings of ICA, pp.975-980, 2003.

L. Parra and C. Spence, On-line convolutive blind source separation of non-stationary signals Journal of VLSI signal processing systems for signal, image and video technology, pp.39-46, 2000.

J. Anemüller and T. Gramss, On-line blind separation of moving sound sources, Proceedings of ICA, 1998.

S. Gazor and Z. Wei, Speech probability distribution, IEEE Signal Processing Letters, vol.10, issue.7, pp.204-207, 2003.
DOI : 10.1109/LSP.2003.813679

R. Martin and C. Breithaupt, Speech enhancement in the DFT domain using Laplacian speech priors, International Workshop on Acoustic Signal Enhancement, 2003.

I. Cohen, Speech enhancement using super-Gaussian speech models and noncausal a priori SNR estimation, Speech Communication, vol.47, issue.3, pp.336-350, 2005.
DOI : 10.1016/j.specom.2005.02.011

Y. Liang, G. Chen, S. Naqvi, and J. Chambers, Independent vector analysis with multivariate student's t-distribution source prior for speech separation, Electronics Letters, vol.49, issue.16, 2013.
DOI : 10.1049/el.2013.1999

D. M. Ritchie and B. W. Kernighan, The C Programming Language, 1975.
DOI : 10.1007/978-3-662-09507-2_22

J. F. Blinn, Floating-point tricks, IEEE Computer Graphics and Applications, vol.17, issue.4, pp.80-84, 1997.
DOI : 10.1109/38.595279

V. Hamacher, J. Chalupper, J. Eggers, E. Fischer, U. Kornagel et al., Signal Processing in High-End Hearing Aids: State of the Art, Challenges, and Future Trends, EURASIP Journal on Advances in Signal Processing, vol.2005, issue.18, pp.2915-2929, 2005.
DOI : 10.1155/ASP.2005.2915

R. Mukai, H. Sawada, S. Araki, and S. Makino, Blind source separation for moving speech signals using blockwise ICA and residual crosstalk subtraction, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol.87, issue.8, pp.1941-1948, 2004.

K. Reindl, Y. Zheng, and W. Kellermann, Speech enhancement for binaural hearing aids based on blind source separation, 2010 4th International Symposium on Communications, Control and Signal Processing (ISCCSP), pp.1-6, 2010.
DOI : 10.1109/ISCCSP.2010.5463317

H. Sheikhzadeh, R. Brennan, and H. Sameti, Real-time implementation of HMM-based MMSE algorithm for speech enhancement in hearing aid applications, 1995 International Conference on Acoustics, Speech, and Signal Processing, pp.808-811, 1995.
DOI : 10.1109/ICASSP.1995.479817

L. C. Parra and C. V. Alvino, Geometric source separation: merging convolutive source separation with geometric beamforming, IEEE Transactions on Speech and Audio Processing, vol.10, issue.6, pp.352-362, 2002.
DOI : 10.1109/TSA.2002.803443

M. Z. Ikram and D. Morgan, A beamforming approach to permutation alignment for multichannel frequency-domain blind speech separation, IEEE International Conference on Acoustics, Speech, and Signal Processing, p.881, 2002.

K. Kim, T. H. Chalidabhongse, D. Harwood, and L. Davis, Real-time foreground???background segmentation using codebook model, Real-Time Imaging, vol.11, issue.3, pp.172-185, 2005.
DOI : 10.1016/j.rti.2004.12.004

R. Y. Tsai, A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses, IEEE Journal on Robotics and Automation, vol.3, issue.4, pp.323-344, 1987.
DOI : 10.1109/JRA.1987.1087109

P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, p.511, 2001.
DOI : 10.1109/CVPR.2001.990517

Y. Liang, J. Harris, G. Chen, S. Naqvi, C. Jutten et al., Auxiliary function based Independent Vector Analysis using a source prior exploiting fourth order relationships, p.2013

Y. Liang, S. M. Naqvi, and J. A. Chambers, Adaptive step size independent vector analysis for blind source separation, 17th International Conference on Digital Signal Processing, pp.1-6, 2011.

S. Cecchi, A. Primavera, F. Piazza, and A. Carini, An adaptive multiple position room response equalizer, 2011.

S. Elliott and P. Nelson, Multiple-point equalization in a room using adaptive digital filters, Journal of the Audio Engineering Society, vol.37, issue.11, pp.899-907, 1989.