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, 2014. ,
DOI : 10.1109/MSP.2013.2297440
URL : https://hal.archives-ouvertes.fr/hal-00922378
Sparse Component Analysis, " in Handbook of Blind Source Separation, Independent Component Analysis and Applications, pp.367-420, 2010. ,
Map-based underdetermined blind source separation of convolutive mixtures by hierarchical clustering and l1-norm minimization, EURASIP Journal on Applied Signal Processing, vol.2007, issue.1, pp.81-81, 2007. ,
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
Complex Nonconvex l p Norm Minimization for Underdetermined Source Separation, Proc. Int. Conf. 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
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
Probabilistic Modeling Paradigms for Audio Source Separation, Machine Audition: Principles, Algorithms and Systems, W. Wang, pp.162-185, 2010. ,
DOI : 10.4018/978-1-61520-919-4.ch007
URL : https://hal.archives-ouvertes.fr/inria-00544016
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
Compositional Models for Audio Processing: Uncovering the structure of sound mixtures, IEEE Signal Processing Magazine, vol.32, issue.2, pp.125-144, 2015. ,
DOI : 10.1109/MSP.2013.2288990
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
Nonnegative matrix factorization with the Itakura-Saito divergence: With application to music analysis Bayesian extensions to nonnegative matrix factorisation for audio signal modelling, Proc. IEEE Int, pp.793-830, 2008. ,
Cauchy nonnegative matrix factorization, 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.1-5, 2015. ,
DOI : 10.1109/WASPAA.2015.7336900
URL : https://hal.archives-ouvertes.fr/hal-01170924
Alpha-stable matrix factorization, IEEE Signal Process. Lett, vol.22, issue.12, pp.2289-2293, 2015. ,
Student's t nonnegative matrix factorization and positive semidefinite tensor factorization for singlechannel audio source separation, Proc. IEEE Int, pp.51-55, 2016. ,
DOI : 10.1109/icassp.2016.7471635
L??vy NMF for robust nonnegative source separation, 2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.259-263, 2017. ,
DOI : 10.1109/WASPAA.2017.8170035
URL : http://arxiv.org/pdf/1608.01844
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
Multichannel Extensions of Non-Negative Matrix Factorization With Complex-Valued Data, IEEE Transactions on Audio, Speech, and Language Processing, vol.21, issue.5, pp.971-982, 2013. ,
DOI : 10.1109/TASL.2013.2239990
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
Student's t multichannel nonnegative matrix factorization for blind source separation, 2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC), pp.1-5, 2016. ,
DOI : 10.1109/IWAENC.2016.7602889
Determined Blind Source Separation Unifying Independent Vector Analysis and Nonnegative Matrix Factorization, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.24, issue.9, pp.1626-1641, 2016. ,
DOI : 10.1109/TASLP.2016.2577880
URL : http://doi.org/10.1109/taslp.2016.2577880
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
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
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
Engineering noise control: theory and practice, 2009. ,
DOI : 10.4324/9780203163900
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
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
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, 2014. ,
DOI : 10.1109/TASLP.2014.2341920
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
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
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.2017-541 ,
DOI : 10.1109/ICASSP.2017.7952214
URL : https://hal.archives-ouvertes.fr/hal-01430754
Reverberant Audio Source Separation via Sparse and Low-Rank Modeling, IEEE Signal Processing Letters, vol.21, issue.4, pp.404-408, 2014. ,
DOI : 10.1109/LSP.2014.2303135
URL : http://arxiv.org/pdf/1312.2795
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), pp.2017-2043 ,
DOI : 10.1109/ICASSP.2017.7951791
URL : https://hal.archives-ouvertes.fr/hal-01416347
Convex Regularizations for the Simultaneous Recording of Room Impulse Responses, IEEE Transactions on Signal Processing, vol.62, issue.8, pp.1976-1986, 2014. ,
DOI : 10.1109/TSP.2014.2303431
URL : https://hal.archives-ouvertes.fr/hal-00934941
Bayesian sparse signal recovery using scale mixtures with applications to speech, 2016. ,
DOI : 10.1109/tsp.2016.2546231
URL : http://arxiv.org/pdf/1507.05087
Preservation of whiteness in spectral and time-frequency transforms of second order processes, Institut Mines-Télécom, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01252189
Scale mixtures of normal distributions, Journal of the Royal Statistical Society. Series B (Methodological ), vol.36, issue.1, pp.99-102, 1974. ,
Variational EM algorithms for non-Gaussian latent variable models, Proc. Adv. Neural Information Process. Syst. (NIPS), pp.1059-1066, 2006. ,
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
Coding-Based Informed Source Separation: Nonnegative Tensor Factorization Approach, IEEE Transactions on Audio, Speech, and Language Processing, vol.21, issue.8, pp.1699-1712, 2013. ,
DOI : 10.1109/TASL.2013.2260153
URL : https://hal.archives-ouvertes.fr/hal-00869603
Multichannel audio database in various acoustic environments, 2014 14th International Workshop on Acoustic Signal Enhancement (IWAENC), pp.313-317, 2014. ,
DOI : 10.1109/IWAENC.2014.6954309
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
Statistical parameters of the frequency response curves of large rooms, Journal of the Audio Engineering Society, vol.35, issue.5, pp.299-306, 1987. ,
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
La transmission de l'´ energie sonore dans les salles, 1988. ,
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, 1962. ,
DOI : 10.1121/1.1909022
Pattern Recognition and Machine Learning, 2006. ,
Variational message passing, Journal of Machine Learning Research, vol.6, pp.661-694, 2005. ,
Variational Inference: A Review for Statisticians, Journal of the American Statistical Association, vol.2, issue.518, pp.859-877, 2017. ,
DOI : 10.1016/j.neuroimage.2007.04.054
URL : http://arxiv.org/pdf/1601.00670
Approximate Riemannian conjugate gradient learning for fixed-form variational Bayes, Journal of Machine Learning Research, vol.11, pp.3235-3268, 2010. ,
Algorithms for Nonnegative Matrix Factorization with the ??-Divergence, Neural Computation, vol.11, issue.9, pp.2421-2456, 2011. ,
DOI : 10.1109/TASL.2009.2034186
Multichannel nonnegative tensor factorization with structured constraints for userguided audio source separation, Proc. IEEE Int, pp.257-260, 2011. ,
DOI : 10.1109/icassp.2011.5946389
URL : https://hal.archives-ouvertes.fr/inria-00564851
Flexible Audio Source Separation Toolbox (FAAST) version 1 for Matlab, 2008. ,
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
BSS Eval Toolbox Version 3.0 for Matlab, 2007. ,
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
Improved Perceptual Metrics for the Evaluation of Audio Source Separation, Proc. Int. Conf. Latent Variable Analysis and Signal Separation, pp.430-437, 2012. ,
DOI : 10.1016/j.sigpro.2011.10.007
URL : https://hal.archives-ouvertes.fr/hal-00653196
PEASS Toolbox Version 2.0 for Matlab, 2011. ,
Hybrid model and structured sparsity for under-determined convolutive audio source separation Companion website, Proc. IEEE Int, pp.6682-6686, 2014. ,
DOI : 10.1109/icassp.2014.6854893
Revisiting Bayesian blind deconvolution, The Journal of Machine Learning Research, vol.15, issue.1, pp.3595-3634, 2014. ,
DOI : 10.1007/978-3-642-40395-8_4
MedleyDB: A multitrack dataset for annotation-intensive MIR research, Proc. Int. Soc. Music Inf. Retrieval Conf. (ISMIR), pp.155-160, 2014. ,
in the field of signal processing. He received the ParisTech Ph.D. Award in 2006, and the Habilitation degree from the he joined the Image, Data, Signal Department of LTCI, Télécom ParisTech, as an Assistant Professor, where he became Associate Professor in 2005. His research interests focus on statistical modeling of nonstationary signals (including adaptive high resolution spectral analysis and Bayesian extensions to NMF), with applications to audio and music (source separation, denoising, dereverberation, multipitch estimation, automatic music transcription, audio coding, audio inpainting) He is a co-author of 30 journal papers, 10) received the State Engineering degree from thé Ecole Polytechnique 2001, and the Ph.D. degree from the ENST in 2005 Speech, and Music Processing and the IEEE/ACM Transactions on Audio, Speech, and Language Processing, 1999. ,