S. Leglaive, R. Badeau, and G. Richard, Autoregressive moving average modeling of late reverberation in the frequency domain, 2016 24th European Signal Processing Conference (EUSIPCO), 2016.
DOI : 10.1109/EUSIPCO.2016.7760494

URL : https://hal.archives-ouvertes.fr/hal-01322937

S. Leglaive, R. Badeau, and G. Richard, Multichannel audio source separation: Variational inference of time-frequency sources from time-domain observations, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
DOI : 10.1109/ICASSP.2017.7951791

URL : https://hal.archives-ouvertes.fr/hal-01416347

S. Leglaive, U. Sim¸seklisim¸sekli, A. Liutkus, R. Badeau, and G. Richard, Alpha-stable multichannel audio source separation, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
DOI : 10.1109/ICASSP.2017.7952221

URL : https://hal.archives-ouvertes.fr/hal-01416366

S. Leglaive, R. Badeau, and G. Richard, Semi-blind student's t source separation for multichannel audio convolutive mixtures, 2017 25th European Signal Processing Conference (EUSIPCO), 2017.
DOI : 10.23919/EUSIPCO.2017.8081612

URL : https://zenodo.org/record/1159328/files/1570342184.pdf

S. Leglaive, R. Badeau, and G. Richard, «Séparation de sources audio en milieu réverbérant : Factorisation en matrices non-négatives et représentation temporelle du mélange convolutif», 2017.

S. Leglaive, R. Badeau, and G. Richard, «Separating time-frequency sources from time-domain convolutive mixtures using non-negative matrix factorization», dans les actes de : IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)

T. Adali, P. J. Schreier, and L. L. Scharf, Complex-Valued Signal Processing: The Proper Way to Deal With Impropriety, IEEE Transactions on Signal Processing, vol.59, issue.11, pp.5101-5125, 2011.
DOI : 10.1109/TSP.2011.2162954

URL : http://www.csee.umbc.edu/~adali/pubs/IEEEpubs/TSP2011adali.pdf

K. Adilo?-glu, E. Et, and . Vincent, Variational Bayesian Inference for Source Separation and Robust Feature Extraction, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.24, issue.10, pp.1746-1758
DOI : 10.1109/TASLP.2016.2583794

A. Aissa-el-bey, K. Abed-meraim, and Y. Grenier, Blind Separation of Underdetermined Convolutive Mixtures Using Their Time???Frequency Representation, IEEE Transactions on Audio, Speech, and Language Processing, vol.15, issue.5, pp.1540-1550, 2007.
DOI : 10.1109/TASL.2007.898455

J. B. Allen, D. A. Et, and . Berkley, Image method for efficiently simulating small???room acoustics, The Journal of the Acoustical Society of America, vol.65, issue.4, pp.943-950, 1979.
DOI : 10.1121/1.382599

D. F. Andrews, C. L. Et, and . Mallows, «Scale mixtures of normal distributions», Journal of the Royal Statistical Society. Series B (Methodological), vol.36, issue.1, pp.99-102, 1974.

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), pp.1-4, 2010.
DOI : 10.1109/ISSPA.2010.5605570

URL : https://hal.archives-ouvertes.fr/inria-00541436

S. Arberet, P. Et, and . Vandergheynst, Reverberant Audio Source Separation via Sparse and Low-Rank Modeling, IEEE Signal Processing Letters, vol.21, issue.4, pp.404-408
DOI : 10.1109/LSP.2014.2303135

URL : http://arxiv.org/pdf/1312.2795

H. Attias, New EM algorithms for source separation and deconvolution with a microphone array, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., pp.297-300, 2003.
DOI : 10.1109/ICASSP.2003.1199930

URL : http://research.goldenmetallic.com/icassp03_bss.pdf

Y. Avargel, I. Et, and . Cohen, On Multiplicative Transfer Function Approximation in the Short-Time Fourier Transform Domain, IEEE Signal Processing Letters, vol.14, issue.5, pp.337-340, 2007.
DOI : 10.1109/LSP.2006.888292

Y. Avargel, I. Et, and . Cohen, System Identification in the Short-Time Fourier Transform Domain With Crossband Filtering, IEEE Transactions on Audio, Speech and Language Processing, vol.15, issue.4, pp.1305-1319, 2007.
DOI : 10.1109/TASL.2006.889720

R. Badeau, 2016, «Preservation of whiteness in spectral and time-frequency transforms of second order processes», Rapport de recherche, Institut Mines-Télécom, p.87

R. Badeau, N. Bertin, and E. Vincent, Stability Analysis of Multiplicative Update Algorithms and Application to Nonnegative Matrix Factorization, IEEE Transactions on Neural Networks, vol.21, issue.12, pp.1869-1881, 2010.
DOI : 10.1109/TNN.2010.2076831

URL : https://hal.archives-ouvertes.fr/inria-00555984

R. Badeau, M. D. Et, and . Plumbley, Multichannel High-Resolution NMF for Modeling Convolutive Mixtures of Non-Stationary Signals in the Time-Frequency Domain, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.22, issue.11, pp.1670-1680
DOI : 10.1109/TASLP.2014.2341920

D. Barchiesi, M. D. Et, and . Plumbley, Dictionary learning of convolved signals, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.5812-5815, 2011.
DOI : 10.1109/ICASSP.2011.5947682

URL : https://hal.archives-ouvertes.fr/hal-00705998

J. Barzilai, J. M. Et, and . Borwein, Two-Point Step Size Gradient Methods, IMA Journal of Numerical Analysis, vol.8, issue.1, pp.141-148, 1988.
DOI : 10.1093/imanum/8.1.141

A. Belouchrani, K. Abed-meraim, J. Cardoso, and E. Moulines, A blind source separation technique using second-order statistics, IEEE Transactions on Signal Processing, vol.45, issue.2, pp.434-444, 1997.
DOI : 10.1109/78.554307

URL : http://www.ece.vill.edu/user/adel/mypapers/ieeesobi.ps.gz

L. Benaroya, L. Mcdonagh, 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

A. Benichoux, L. S. Simon, E. Vincent, and R. Gribonval, Convex Regularizations for the Simultaneous Recording of Room Impulse Responses, IEEE Transactions on Signal Processing, vol.62, issue.8, pp.1976-1986
DOI : 10.1109/TSP.2014.2303431

URL : https://hal.archives-ouvertes.fr/hal-00934941

N. Bertin, E. Camberlein, E. Vincent, R. Lebarbenchon, S. Peillon et al., «A French corpus for distantmicrophone speech processing in real homes», p.133, 2016.

D. A. Bies and C. H. Hansen, Engineering noise control : theory and practice, pp.59-139, 2009.
DOI : 10.4324/9780203163900

E. Bingham, A. Et, and . 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

R. M. Bittner, J. Salamon, M. Tierney, M. Mauch, C. Cannam et al., «MedleyDB : A multitrack dataset for annotation-intensive MIR research, dans Actes de International Society for Music Information Retrieval (ISMIR) Conference, pp.155-160, 2014.

G. Bongiovanni, P. Corsini, and G. Frosini, One-dimensional and two-dimensional generalised discrete fourier transforms, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.24, issue.1, pp.97-99, 1976.
DOI : 10.1109/TASSP.1976.1162764

J. J. Carabias-orti, M. Cobos, P. Vera-candeas, and F. J. Rodríguez-serrano, Nonnegative signal factorization with learnt instrument models for sound source separation in close-microphone recordings, EURASIP Journal on Advances in Signal Processing, vol.19, issue.7, pp.184-189
DOI : 10.1109/TASL.2011.2109381

J. Cardoso, Blind signal separation: statistical principles, Proceedings of the IEEE, vol.86, issue.10, pp.2009-2025, 1998.
DOI : 10.1109/5.720250

URL : http://www.cmap.polytechnique.fr/~peyre/cours/x2003signal/bss_tutorial.pdf

B. P. Carlin, T. A. Et, and . Louis, Bayesian methods for data analysis, p.138, 2008.

A. T. Cemgil, C. Févotte, and S. J. , Variational and stochastic inference for Bayesian source separation, Digital Signal Processing, vol.17, issue.5, pp.891-913, 2007.
DOI : 10.1016/j.dsp.2007.03.008

URL : http://perso.telecom-paristech.fr/~fevotte/Journals/elsevier_dsp_variational.pdf

M. Chion, Guide des objets sonores : Pierre Schaeffer et la recherche musicale, Buchet/Chastel, p.4, 1983.

A. Cichocki and S. Amari, Families of Alpha- Beta- and Gamma- Divergences: Flexible and Robust Measures of Similarities, Entropy, vol.45, issue.12, pp.1532-1568, 2010.
DOI : 10.1093/biomet/88.3.865

P. Comon, «Independent component analysis, a new concept ?», Signal processing, pp.287-314, 1994.

U. Sim¸seklisim¸sekli, A. Liutkus, and A. T. , Alpha-Stable Matrix Factorization, IEEE Signal Processing Letters, vol.22, issue.12, pp.2289-2293
DOI : 10.1109/LSP.2015.2477535

G. Darmois, Analyse generale des liaisons stochastiques: etude particuliere de l'analyse factorielle lineaire, Revue de l'Institut International de Statistique / Review of the International Statistical Institute, vol.21, issue.1/2, pp.2-8, 1953.
DOI : 10.2307/1401511

A. Deleforge, F. Forbes, and R. Horaud, Acoustic Space Learning for Sound-Source Separation and Localization on Binaural Manifolds, International Journal of Neural Systems, vol.7, issue.01, pp.1440-1443, 2015.
DOI : 10.1109/TSA.2005.858005

URL : https://hal.archives-ouvertes.fr/hal-00960796

A. P. Dempster, N. M. Laird, and D. B. Rubin, «Maximum likelihood from incomplete data via the EM algorithm», Journal of the royal statistical society. Series B (methodological), pp.1-38, 1977.

N. Q. Duong, E. Vincent, and R. Gribonval, Under-Determined Reverberant Audio Source Separation Using a Full-Rank Spatial Covariance Model, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.7, pp.1830-1840, 2010.
DOI : 10.1109/TASL.2010.2050716

URL : https://hal.archives-ouvertes.fr/inria-00541865

N. Q. Duong, E. Vincent, and R. Gribonval, Spatial location priors for Gaussian model based reverberant audio source separation, EURASIP Journal on Advances in Signal Processing, vol.92, issue.4, pp.149-186
DOI : 10.1007/978-3-642-15995-4_8

URL : https://hal.archives-ouvertes.fr/hal-00870191

J. Durbin, «Efficient estimation of parameters in moving-average models», Biometrika, vol.464, issue.3, pp.306-316, 1959.

J. Durrieu, B. David, and G. Richard, A Musically Motivated Mid-Level Representation for Pitch Estimation and Musical Audio Source Separation, IEEE Journal of Selected Topics in Signal Processing, vol.5, issue.6, pp.1180-1191, 2011.
DOI : 10.1109/JSTSP.2011.2158801

J. Durrieu, G. Richard, B. David, and C. Févotte, Source/Filter Model for Unsupervised Main Melody Extraction From Polyphonic Audio Signals, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.3, pp.564-575, 2010.
DOI : 10.1109/TASL.2010.2041114

URL : http://perso.telecom-paristech.fr/~grichard/Publications/TSALP_Durrieu10.pdf

V. Emiya, E. Vincent, N. Harlander, and V. Hohmann, Subjective and Objective Quality Assessment of Audio Source Separation, IEEE Transactions on Audio, Speech, and Language Processing, vol.19, issue.7, pp.2046-2057, 2011.
DOI : 10.1109/TASL.2011.2109381

URL : https://hal.archives-ouvertes.fr/inria-00567152

F. Feng, M. Et, and . Kowalski, 2014, «Hybrid model and structured sparsity for under-determined convolutive audio source separation», dans Actes de IEEE International Conference on Acoustics, Speech and Signal Processing, pp.6682-6686
DOI : 10.1109/icassp.2014.6854893

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

C. Févotte and S. J. Et, A Bayesian Approach for Blind Separation of Sparse Sources, IEEE Transactions on Audio, Speech and Language Processing, vol.14, issue.6, pp.2174-2188, 2006.
DOI : 10.1109/TSA.2005.858523

C. Févotte, J. Et, and . Idier, Algorithms for Nonnegative Matrix Factorization with the ??-Divergence, Neural Computation, vol.11, issue.9, pp.2421-2456, 2011.
DOI : 10.1109/TASL.2009.2034186

C. Févotte, M. Et, and . Kowalski, 2014, «Low-rank time-frequency synthesis», Actes de Advances in Neural Information Processing Systems (NIPS), pp.3563-3571

M. Fontaine, C. Vanwynsberghe, A. Liutkus, and R. Badeau, «Scalable Source Localization with Multichannel Alpha-Stable Distributions», dans Actes de European Signal Processing Conference (EUSIPCO), Actes de European Signal Processing Conference (EUSIPCO), pp.11-15, 2017.
DOI : 10.23919/eusipco.2017.8081159

M. Fontaine, C. Vanwynsberghe, A. Liutkus, and R. Badeau, Sketching for Nearfield Acoustic Imaging of Heavy-Tailed Sources, dans Actes de International Conference on Latent Variable Analysis and Signal Separation, pp.80-88, 2017.
DOI : 10.1109/TSA.2004.832990

URL : https://hal.archives-ouvertes.fr/hal-01401988

A. Fraysse and T. Rodet, A Measure-Theoretic Variational Bayesian Algorithm for Large Dimensional Problems, SIAM Journal on Imaging Sciences, vol.7, issue.4, pp.2591-2622, 2014.
DOI : 10.1137/140966575

URL : https://hal.archives-ouvertes.fr/hal-00702259

S. Gannot, E. Vincent, S. Markovich-golan, and A. Ozerov, A Consolidated Perspective on Multimicrophone Speech Enhancement and Source Separation, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.25, issue.4, pp.692-730, 2017.
DOI : 10.1109/TASLP.2016.2647702

URL : https://hal.archives-ouvertes.fr/hal-01414179

J. Ganseman, P. Scheunders, G. J. Mysore, and J. S. Abel, «Evaluation of a score-informed source separation system, dans Actes de International Society for Music Information Retrieval (ISMIR) Conference, pp.219-224, 2010.

C. Gilavert, S. Moussaoui, and J. Idier, Efficient Gaussian Sampling for Solving Large-Scale Inverse Problems Using MCMC, IEEE Transactions on Signal Processing, vol.63, issue.1, pp.70-80
DOI : 10.1109/TSP.2014.2367457

URL : https://hal.archives-ouvertes.fr/hal-01059414

R. Giri, Bayesian sparse signal recovery using scale mixtures with applications to speech, p.108, 2016.
DOI : 10.1109/tsp.2016.2546231

URL : http://arxiv.org/pdf/1507.05087

R. Gribonval, M. Et, and . Zibulevsky, «Sparse component analysis», dans Handbook of Blind Source Separation, Independent Component Analysis and Applications, édité par P. Comon et C. Jutten, Academic press, pp.367-420, 2010.

G. Gu, X. Gao, J. He, and M. Naraghi-pour, «Parametric modeling of wideband and ultrawideband channels in frequency domain», IEEE Transactions on Vehicular Technology, vol.56, issue.4, pp.1600-1612, 2007.

T. Gustafsson, B. D. Rao, and M. Trivedi, Source localization in reverberant environments: modeling and statistical analysis, IEEE Transactions on Speech and Audio Processing, vol.11, issue.6, pp.791-803, 2003.
DOI : 10.1109/TSA.2003.818027

URL : http://www.itr-rescue.org/pubs/upload/335_Gustafsson,2005.pdf

T. Heittola, A. Klapuri, and T. Virtanen, «Musical instrument recognition in polyphonic audio using source-filter model for sound separation, dans Actes de International Society for Music Information Retrieval (ISMIR) Conference, pp.327-332, 2009.

R. Hennequin, B. David, and R. Badeau, Score informed audio source separation using a parametric model of non-negative spectrogram, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.45-48, 2011.
DOI : 10.1109/ICASSP.2011.5946324

URL : https://hal.archives-ouvertes.fr/hal-00945294

J. Hérault, C. Jutten, and B. Ans, «Détection de grandeurs primitives dans un message composite par une architecture de calcul neuromimétique en apprentissage non supervisé», dans Colloque sur le traitement du signal et des images, GRETSI, Groupe d, Etudes du Traitement du Signal et des Images, vol.21, pp.1017-1022, 1985.

M. R. Hestenes, E. Et, and . Stiefel, Methods of conjugate gradients for solving linear systems, p.143, 1952.

A. Honkela, T. Raiko, M. Kuusela, M. Tornio, and J. Karhunen, «Approximate Riemannian conjugate gradient learning for fixed-form variational Bayes», Journal of Machine Learning Research, vol.11, issue.118, pp.3235-3268, 2010.

D. R. Hunter, K. Et, and . Lange, «A tutorial on MM algorithms», The American Statistician, pp.30-37, 2004.

A. Hyvärinen and E. Oja, Independent component analysis: algorithms and applications, Neural Networks, vol.13, issue.4-5, pp.411-430, 2000.
DOI : 10.1016/S0893-6080(00)00026-5

J. Jot, L. Cerveau, and O. Warusfel, «Analysis and synthesis of room reverberation based on a statistical time-frequency model», dans Audio Engineering Society Convention 103, p.53, 1997.

H. Kameoka, N. Ono, and S. Sagayama, «Auxiliary function approach to parameter estimation of constrained sinusoidal model for monaural speech separation», dans Actes de IEEE International Conference on Acoustics, Speech and Signal Processing, pp.29-32, 2008.

S. Kay, «Spectral estimation», dans Advanced Topics in Signal Processing, édité par J. S. Lim et A. V. Oppenheim, pp.58-122, 1988.

D. P. Kingma, Variational inference and deep learning : A new synthesis, pp.116-132, 2017.

S. Kotz, S. Et, and . Nadarajah, Multivariate t-distributions and their applications, p.137, 2004.

D. Kounades-bastian, L. Girin, X. Alameda-pineda, S. Gannot, and R. Horaud, A variational EM algorithm for the separation of moving sound sources, 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.1-5, 2015.
DOI : 10.1109/WASPAA.2015.7336936

URL : https://hal.archives-ouvertes.fr/hal-01169764

D. Kounades-bastian, L. Girin, X. Alameda-pineda, S. Gannot, and R. Horaud, 2016, «An inversegamma source variance prior with factorized parameterization for audio source separation», dans Actes de IEEE International Conference on Acoustics, Speech and Signal Processing, pp.136-140
DOI : 10.1109/icassp.2016.7471652

M. Kowalski, E. Vincent, and R. Gribonval, Beyond the Narrowband Approximation: Wideband Convex Methods for Under-Determined Reverberant Audio Source Separation, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.7, pp.1818-1829, 2010.
DOI : 10.1109/TASL.2010.2050089

URL : https://hal.archives-ouvertes.fr/hal-00435897

R. Kumaresan, On the zeros of the linear prediction-error filter for deterministic signals, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.31, issue.1, pp.217-220, 1983.
DOI : 10.1109/TASSP.1983.1164021

H. Kuttruff, Room acoustics, p.56, 2009.

D. D. Lee and H. S. Seung, «Learning the parts of objects by non-negative matrix factorization», Nature, vol.401, pp.6755-788, 1999.

S. Leglaive, R. Badeau, and G. Richard, «A priori probabiliste anéchoïque pour la séparation sous-déterminée de sources sonores en milieu réverbérant», dans Colloque GRETSI. Papier no, pp.15-55, 2015.

S. Leglaive, R. Badeau, and G. Richard, Multichannel audio source separation with probabilistic reverberation modeling, 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.1-5, 2015.
DOI : 10.1109/WASPAA.2015.7336932

URL : https://hal.archives-ouvertes.fr/hal-01219635

S. Leglaive, R. Badeau, and G. Richard, Autoregressive moving average modeling of late reverberation in the frequency domain, 2016 24th European Signal Processing Conference (EUSIPCO), pp.1478-1482, 2016.
DOI : 10.1109/EUSIPCO.2016.7760494

URL : https://hal.archives-ouvertes.fr/hal-01322937

S. Leglaive, R. Badeau, and G. Richard, Multichannel Audio Source Separation With Probabilistic Reverberation Priors, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.24, issue.12, pp.2453-2465, 2016.
DOI : 10.1109/TASLP.2016.2614140

URL : https://hal.archives-ouvertes.fr/hal-01370051

S. Leglaive, R. Badeau, and G. Richard, 2017a, «Multichannel audio source separation : variational inference of time-frequency sources from time-domain observations», dans Actes de IEEE International Conference on Acoustics, Speech and Signal Processing, pp.26-30

S. Leglaive, R. Badeau, and G. Richard, Semi-blind student's t source separation for multichannel audio convolutive mixtures, 2017 25th European Signal Processing Conference (EUSIPCO), pp.2323-2327, 2017.
DOI : 10.23919/EUSIPCO.2017.8081612

URL : https://zenodo.org/record/1159328/files/1570342184.pdf

S. Leglaive, R. Badeau, and G. Richard, «Separating time-frequency sources from timedomain convolutive mixtures using non-negative matrix factorization», dans Actes de IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.264-268, 2017.
DOI : 10.1109/waspaa.2017.8170036

S. Leglaive, R. Badeau, and G. Richard, 2017d, «Student's t source and mixing models for multichannel audio source separation», IEEE Transactions on Audio, Speech, and Language Processing, vol.108, p.17

S. Leglaive, R. Hennequin, and R. Badeau, Singing voice detection with deep recurrent neural networks, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.121-125, 2015.
DOI : 10.1109/ICASSP.2015.7177944

URL : https://hal.archives-ouvertes.fr/hal-01110035

X. Li, L. Girin, and R. Horaud, Audio source separation based on convolutive transfer function and frequency-domain lasso optimization, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.541-545, 2017.
DOI : 10.1109/ICASSP.2017.7952214

URL : https://hal.archives-ouvertes.fr/hal-01430754

X. Li, L. Girin, and R. Horaud, An em algorithm for audio source separation based on the convolutive transfer function, 2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.56-60, 2017.
DOI : 10.1109/WASPAA.2017.8169994

URL : https://hal.archives-ouvertes.fr/hal-01568818

X. Li, L. Girin, R. Horaud, and S. Gannot, Estimation of the Direct-Path Relative Transfer Function for Supervised Sound-Source Localization, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.24, issue.11, pp.2171-2186
DOI : 10.1109/TASLP.2016.2598319

URL : https://hal.archives-ouvertes.fr/hal-01349691

X. Li, L. Girin, R. Horaud, and S. Gannot, 2017c, «Multiple-speaker localization based on directpath features and likelihood maximization with spatial sparsity regularization», IEEE Transactions on Audio, Speech, and Language Processing, p.133
DOI : 10.1109/taslp.2017.2740001

URL : http://arxiv.org/pdf/1611.01172

A. Lindau, L. Kosanke, and S. Weinzierl, «Perceptual evaluation of physical predictors of the mixing time in binaural room impulse responses», dans Audio Engineering Society Convention 128, p.53, 2010.

A. Liutkus, Processus gaussiens pour la séparation de sources et le codage informé, thèse de doctorat, Télécom ParisTech, p.26, 2012.

A. Liutkus, R. Badeau, and G. Richard, Gaussian Processes for Underdetermined Source Separation, IEEE Transactions on Signal Processing, vol.59, issue.7, pp.3155-3167, 2011.
DOI : 10.1109/TSP.2011.2119315

URL : https://hal.archives-ouvertes.fr/hal-00643951

A. Liutkus, F. Stöter, Z. Rafii, D. Kitamura, B. Rivet et al., 2017, «The 2016 Signal Separation Evaluation Campaign», 13th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2017), pp.323-332
DOI : 10.1007/978-3-319-53547-0_31

P. Magron, R. Badeau, and A. Liutkus, 2017, «Lévy NMF for robust nonnegative source separation», dans Actes de IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.259-263
DOI : 10.1109/waspaa.2017.8170035

URL : http://arxiv.org/pdf/1608.01844

H. S. Malvar, Signal Processing with Lapped Transforms, Artech House, 1992.
DOI : 10.1109/icassp.1990.115698

M. I. Mandel, R. J. Weiss, and D. P. Ellis, Model-Based Expectation-Maximization Source Separation and Localization, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.2, pp.382-394, 2010.
DOI : 10.1109/TASL.2009.2029711

URL : http://www.ee.columbia.edu/%7Eronw/pubs/taslp09-messl.pdf

A. Mertins, Signal Analysis : Wavelets, Filter Banks, Time-Frequency Transforms and Applications, p.11, 1999.
DOI : 10.1002/0470841834

J. A. Moorer, About This Reverberation Business, Computer Music Journal, vol.3, issue.2, pp.13-28, 1979.
DOI : 10.2307/3680280

URL : http://www.bagger288.com/temp/aboutThisReverberationBusiness.pdf

S. Nakamura, K. Hiyane, F. Asano, T. Nishiura, and T. Yamada, «Acoustical sound database in real environments for sound scene understanding and hands-free speech recognition, dans Actes de International Conference on Language Resources and Evaluation (LREC), pp.965-968, 2000.

A. Nugraha, A. Liutkus, and E. Vincent, Multichannel Audio Source Separation With Deep Neural Networks, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.24, issue.9, pp.1652-1664, 2016.
DOI : 10.1109/TASLP.2016.2580946

URL : https://hal.archives-ouvertes.fr/hal-01163369

A. Nugraha, A. Liutkus, and E. Vincent, 2016b, «Multichannel music separation with deep neural networks», dans Actes de European Signal Processing Conference (EUSIPCO), pp.1748-1752
DOI : 10.1109/eusipco.2016.7760548

A. Ozerov and C. Févotte, Multichannel Nonnegative Matrix Factorization in Convolutive Mixtures for Audio Source Separation, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.3, pp.550-563, 2010.
DOI : 10.1109/TASL.2009.2031510

A. Ozerov, C. Févotte, R. Blouet, and J. Durrieu, Multichannel nonnegative tensor factorization with structured constraints for user-guided audio source separation, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.257-260, 2011.
DOI : 10.1109/ICASSP.2011.5946389

URL : https://hal.archives-ouvertes.fr/inria-00564851

A. Ozerov, E. Vincent, and F. Bimbot, A General Flexible Framework for the Handling of Prior Information in Audio Source Separation, IEEE Transactions on Audio, Speech, and Language Processing, vol.20, issue.4, pp.1118-1133, 2012.
DOI : 10.1109/TASL.2011.2172425

URL : https://hal.archives-ouvertes.fr/inria-00536917

J. Palmer, K. Kreutz-delgado, B. D. Rao, and D. P. Wipf, «Variational EM algorithms for non- Gaussian latent variable models», dans Advances in neural information processing systems, pp.1059-1066, 2006.

L. Parra, C. Et, and . 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

D. Pham, J. Et, and . Cardoso, Blind separation of instantaneous mixtures of nonstationary sources, IEEE Transactions on Signal Processing, vol.49, issue.9, pp.1837-1848, 2001.
DOI : 10.1109/78.942614

J. Polack, La transmission de l'énergie sonore dans les salles, pp.56-110, 1988.

J. Polack, Playing billiards in the concert hall: The mathematical foundations of geometrical room acoustics, Applied Acoustics, vol.38, issue.2-4, pp.235-244, 1993.
DOI : 10.1016/0003-682X(93)90054-A

T. Prätzlich, R. M. Bittner, A. Liutkus, and M. Müller, 2015, «Kernel additive modeling for interference reduction in multi-channel music recordings», dans Actes de IEEE International Conference on Acoustics, Speech and Signal Processing, pp.584-588

C. G. Puntonet, A. Et, and . Prieto, An adaptive geometrical procedure for blind separation of sources, Neural Processing Letters, pp.23-27, 1995.
DOI : 10.1007/BF02332162

B. D. Radlovic, R. C. Williamson, and R. A. Kennedy, Equalization in an acoustic reverberant environment: robustness results, IEEE Transactions on Speech and Audio Processing, vol.8, issue.3, pp.311-319, 2000.
DOI : 10.1109/89.841213

R. Ratnam, D. L. Jones, B. C. Wheeler, W. D. O-'brien-jr, C. R. Lansing et al., Blind estimation of reverberation time, The Journal of the Acoustical Society of America, vol.114, issue.5, pp.2877-2892, 2003.
DOI : 10.1121/1.1616578

S. Rickard, «The duet blind source separation algorithm», dans Blind Speech Separation, pp.217-241, 2007.

G. Samorodnitsky, M. S. Et, and . Taqqu, Stable non-Gaussian random processes : stochastic models with infinite variance, p.27, 1994.

H. Sawada, S. Araki, R. Mukai, and S. Makino, Solving the Permutation Problem of Frequency-Domain BSS when Spatial Aliasing Occurs with Wide Sensor Spacing, 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, pp.77-80, 2006.
DOI : 10.1109/ICASSP.2006.1661216

H. Sawada, S. Araki, R. Mukai, and S. Makino, Grouping Separated Frequency Components by Estimating Propagation Model Parameters in Frequency-Domain Blind Source Separation, IEEE Transactions on Audio, Speech and Language Processing, vol.15, issue.5, pp.1592-1604, 2007.
DOI : 10.1109/TASL.2007.899218

URL : http://www.kecl.ntt.co.jp/icl/signal/sawada/mypaper/IEEEtaslp2007sawada.pdf

P. Schaeffer, Traité des objets musicaux, Collection Pierres Vives, Éditions du Seuil, p.4, 1966.

M. N. Schmidt and H. Laurberg, Nonnegative Matrix Factorization with Gaussian Process Priors, Computational Intelligence and Neuroscience, vol.137, issue.1, pp.3-33, 2008.
DOI : 10.1006/jmre.1998.1639

URL : https://doi.org/10.1155/2008/361705

M. R. Schroeder, Frequency???Correlation Functions of Frequency Responses in Rooms, The Journal of the Acoustical Society of America, vol.34, issue.12, pp.1819-1823, 1962.
DOI : 10.1121/1.1909136

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

M. R. Schroeder, «Statistical parameters of the frequency response curves of large rooms», Journal of the Audio Engineering Society, vol.35, issue.5, pp.299-306, 1987.

M. R. Schroeder, K. Et, and . Kuttruff, On Frequency Response Curves in Rooms. Comparison of Experimental, Theoretical, and Monte Carlo Results for the Average Frequency Spacing between Maxima, The Journal of the Acoustical Society of America, vol.34, issue.1, pp.76-80
DOI : 10.1121/1.1909022

T. Schultz, Diffusion in reverberation rooms, Journal of Sound and Vibration, vol.16, issue.1, pp.17-28, 1971.
DOI : 10.1016/0022-460X(71)90392-0

S. Sivasankaran, E. Vincent, and I. Illina, A combined evaluation of established and new approaches for speech recognition in varied reverberation conditions, Computer Speech & Language, vol.46, pp.444-460, 2017.
DOI : 10.1016/j.csl.2017.02.003

URL : https://hal.archives-ouvertes.fr/hal-01461382

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

P. Smaragdis, G. J. Et, and . Mysore, Separation by “humming”: User-guided sound extraction from monophonic mixtures, 2009 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp.69-72, 2009.
DOI : 10.1109/ASPAA.2009.5346542

R. Stewart, M. B. Et, and . Sandler, 2010, «Database of omnidirectional and b-format room impulse responses, dans Actes de IEEE International Conference on Acoustics, Speech and Signal Processing, pp.165-168

H. Tachibana, T. Ono, N. Ono, and S. Sagayama, Melody line estimation in homophonic music audio signals based on temporal-variability of melodic source, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.425-428, 2010.
DOI : 10.1109/ICASSP.2010.5495764

F. J. Theis, A. Jung, C. G. Puntonet, and E. W. Lang, Linear Geometric ICA: Fundamentals and Algorithms, Neural Computation, vol.23, issue.1, pp.419-439, 2003.
DOI : 10.1007/BF00205972

URL : http://hera.ugr.es/doi/14980411.pdf

H. N. Thi, C. Et, and . 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

E. Vincent, Complex Nonconvex l p Norm Minimization for Underdetermined Source Separation, Actes de International Conference on Independent Component Analysis and Blind Source Separation (ICA), pp.430-437, 2007.
DOI : 10.1007/978-3-540-74494-8_54

URL : http://hal.inria.fr/docs/00/54/42/03/PDF/vincent_ICA07bis.pdf

E. Vincent, 2012, «Improved perceptual metrics for the evaluation of audio source separation», dans Actes de International Conference on Latent Variable Analysis and Signal Separation, pp.430-437

E. Vincent, N. Bertin, R. Gribonval, and F. Bimbot, From Blind to Guided Audio Source Separation: How models and side information can improve the separation of sound, IEEE Signal Processing Magazine, vol.31, issue.3, pp.107-115
DOI : 10.1109/MSP.2013.2297440

URL : https://hal.archives-ouvertes.fr/hal-00922378

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

E. Vincent, M. G. Jafari, S. A. Abdallah, M. D. Plumbley, and M. E. Davies, «Probabilistic modeling paradigms for audio source separation», Machine Audition : Principles, Algorithms and Systems, pp.162-185, 2010.
DOI : 10.4018/9781615209194.ch007

URL : http://qmro.qmul.ac.uk/xmlui/bitstream/123456789/5265/2/PLUMBLEYProbabilisticModeling2011POST.pdf

E. Vincent, H. Sawada, P. Bofill, S. Makino, and J. P. Rosca, First Stereo Audio Source Separation Evaluation Campaign: Data, Algorithms and Results, dans Actes de International Conference on Independent Component Analysis and Blind Source Separation, pp.552-559, 2007.
DOI : 10.1007/978-3-540-74494-8_69

URL : https://hal.archives-ouvertes.fr/inria-00544199

T. Virtanen, A. T. Cemgil, and S. Godsill, Bayesian extensions to non-negative matrix factorisation for audio signal modelling, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.1825-1828, 2008.
DOI : 10.1109/ICASSP.2008.4517987

URL : http://www.cmpe.boun.edu.tr/~cemgil/papers/virtanen-cemgil-godsill-icassp08.pdf

T. Virtanen, J. F. Gemmeke, B. Raj, and P. Smaragdis, Compositional Models for Audio Processing: Uncovering the structure of sound mixtures, IEEE Signal Processing Magazine, vol.32, issue.2, pp.125-144
DOI : 10.1109/MSP.2013.2288990

D. Wang, G. J. Et, and . Brown, Computational auditory scene analysis : Principles, algorithms, and applications, 2006.
DOI : 10.1109/9780470043387

L. Wasserman, All of statistics : a concise course in statistical inference, p.39, 2013.
DOI : 10.1007/978-0-387-21736-9

W. Weihua and H. Fenggang, Improved method for solving permutation problem of frequency domain blind source separation, 2008 6th IEEE International Conference on Industrial Informatics, pp.703-706, 2008.
DOI : 10.1109/INDIN.2008.4618192

M. West, «Outlier models and prior distributions in Bayesian linear regression», Journal of the Royal Statistical Society. Series B, pp.431-439, 1984.

M. West, On scale mixtures of normal distributions, Biometrika, vol.74, issue.3, pp.646-648, 1987.
DOI : 10.1093/biomet/74.3.646

J. Winn, C. M. Et, and . Bishop, «Variational message passing», Journal of Machine Learning Research, vol.6, pp.661-694, 2005.

S. Winter, W. Kellermann, H. Sawada, and S. Makino, MAP-Based Underdetermined Blind Source Separation of Convolutive Mixtures by Hierarchical Clustering and -Norm Minimization, EURASIP Journal on Advances in Signal Processing, vol.14, issue.4, pp.24-717, 2007.
DOI : 10.1109/TSA.2005.858005

D. Wipf and H. Zhang, «Revisiting Bayesian blind deconvolution», Journal of Machine Learning Research, vol.15, issue.1, pp.3595-3634, 2014.
DOI : 10.1007/978-3-642-40395-8_4

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

K. Yoshii, K. Itoyama, and M. Goto, 2016, «Student's t nonnegative matrix factorization and positive semidefinite tensor factorization for single-channel audio source separation», dans Actes de IEEE International Conference on Acoustics, Speech and Signal Processing, pp.51-55
DOI : 10.1109/icassp.2016.7471635

Y. Zheng, A. Fraysse, and T. Rodet, Efficient Variational Bayesian Approximation Method Based on Subspace Optimization, IEEE Transactions on Image Processing, vol.24, issue.2, pp.681-693
DOI : 10.1109/TIP.2014.2383321

URL : https://hal.archives-ouvertes.fr/hal-00990003