G. J. Mysore and P. Smaragdis, A non-negative approach to language informed speech separation, " in Latent Variable Analysis and Signal Separation Available: https://ccrma, pp.356-363, 2012.

L. , L. Magoarou, A. Ozerov, and N. Q. Duong, Text-informed audio source separation. example-based approach using nonnegative matrix partial co-factorization, Journal of Signal Processing Systems, pp.1-15, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01010602

D. L. Sun and G. J. Mysore, Universal speech models for speaker independent single channel source separation, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.141-145, 2013.
DOI : 10.1109/ICASSP.2013.6637625

F. G. Germain and G. J. Mysore, Speaker and noise independent online single-channel speech enhancement, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.71-75, 2015.
DOI : 10.1109/ICASSP.2015.7177934

D. S. Williamson, Y. Wang, and D. Wang, Deep neural networks for estimating speech model activations, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.5113-5117, 2015.
DOI : 10.1109/ICASSP.2015.7178945

T. Virtanen and A. Klapuri, Analysis of polyphonic audio using source-filter model and non-negative matrix factorization, Advances in models for acoustic processing, neural information processing systems workshop, 2006.

J. Durrieu, A. Ozerov, C. Févotte, G. Richard, and B. David, Main instrument separation from stereophonic audio signals using a source/filter model, European Signal Processing Conference, pp.15-19, 2009.

D. L. Sun and G. J. Mysore, Universal speech models for speaker independent single channel source separation, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.2013-141
DOI : 10.1109/ICASSP.2013.6637625

F. G. Germain and G. J. Mysore, Speaker and noise independent online single-channel speech enhancement, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.2015-71
DOI : 10.1109/ICASSP.2015.7177934

G. J. Mysore and P. Smaragdis, A non-negative approach to language informed speech separation, " in Latent Variable Analysis and Signal Separation, pp.356-363, 2012.

L. , L. Magoarou, A. Ozerov, and N. Q. Duong, Text-informed audio source separation. Example-based approach using nonnegative matrix partial co-factorization, Journal of Signal Processing Systems, pp.1-15, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01010602

D. D. Lee and H. S. Seung, Learning the parts of objects by non-negative matrix factorization, Nature, vol.401, issue.6755, pp.788-791, 1999.

A. Liutkus, J. Durrieu, L. Daudet, and G. Richard, An overview of informed audio source separation, 2013 14th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS), pp.1-4, 2013.
DOI : 10.1109/WIAMIS.2013.6616139

URL : https://hal.archives-ouvertes.fr/hal-00958661

T. Virtanen, B. Raj, and J. F. Gemmeke, Active-set newton algorithm for non-negative sparse coding of audio, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.3092-3096
DOI : 10.1109/ICASSP.2014.6854169

Y. Wang and D. Wang, A Neural Network For Time-Domain Signal Reconstruction: Towards Improving The Perceptual Quality Of Supervised Speech Separation, 2014.

J. Le-roux, J. R. Hershey, and F. Weninger, Deep NMF for speech separation, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.2015-66
DOI : 10.1109/ICASSP.2015.7177933

L. Benaroya, F. Bimbot, and R. Gribonval, Audio source separation with a single sensor, IEEE Transactions on Audio, Speech and Language Processing, vol.14, issue.1, pp.191-199, 2006.
DOI : 10.1109/TSA.2005.854110

URL : https://hal.archives-ouvertes.fr/inria-00544949

C. Févotte and J. 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

A. Roebel, J. Pons, M. Liuni, and M. Lagrange, On automatic drum transcription using non-negative matrix deconvolution and itakura saito divergence, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.2015-414
DOI : 10.1109/ICASSP.2015.7178002

URL : https://hal.archives-ouvertes.fr/hal-01261256

]. F. Villavicencio, A. Röbel, and X. Rodet, Improving Lpc Spectral Envelope Extraction Of Voiced Speech By True-Envelope Estimation, 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, pp.869-872, 2006.
DOI : 10.1109/ICASSP.2006.1660159

URL : https://hal.archives-ouvertes.fr/hal-01161354

C. Joder, F. Weninger, D. Virette, and B. Schuller, A comparative study on sparsity penalties for NMF-based speech separation: Beyond LP-norms, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.2013-858
DOI : 10.1109/ICASSP.2013.6637770

S. Z. Li, X. W. Hou, H. Zhang, and Q. Cheng, Learning spatially localized, parts-based representation, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, p.207, 2001.
DOI : 10.1109/CVPR.2001.990477

T. Virtanen, Monaural Sound Source Separation by Nonnegative Matrix Factorization With Temporal Continuity and Sparseness Criteria, IEEE Transactions on Audio, Speech and Language Processing, vol.15, issue.3, pp.1066-1074, 2007.
DOI : 10.1109/TASL.2006.885253

T. Virtanen, J. F. Gemmeke, and B. Raj, Active-Set Newton Algorithm for Overcomplete Non-Negative Representations of Audio, IEEE Transactions on Audio, Speech, and Language Processing, vol.21, issue.11, pp.2277-2289, 2013.
DOI : 10.1109/TASL.2013.2263144

V. Zue, S. Seneff, and J. Glass, Speech database development at MIT: Timit and beyond, Speech Communication, vol.9, issue.4, pp.351-356, 1990.
DOI : 10.1016/0167-6393(90)90010-7

D. B. Dean, S. Sridharan, R. J. Vogt, and M. W. Mason, The QUT-NOISE-TIMIT corpus for the evaluation of voice activity detection algorithms, Proceedings of Interspeech 2010, pp.3110-3113, 2010.

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

A. W. Rix, J. G. Beerends, M. P. Hollier, and A. P. Hekstra, Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), pp.749-752, 2001.
DOI : 10.1109/ICASSP.2001.941023