J. M. Baker, L. Deng, J. Glass, S. Khudanpur, C. Lee et al., Developments and directions in speech recognition and understanding, Part 1 [DSP Education], IEEE Signal Processing Magazine, vol.26, issue.3, pp.75-80, 2009.
DOI : 10.1109/MSP.2009.932166

I. Cohen, J. Benesty, and S. Gannot, Speech processing in modern communication: Challenges and perspectives, 2010.
DOI : 10.1007/978-3-642-11130-3

K. S. Rao and S. Sarkar, Robust Speaker Recognition in Noisy Environments, 2014.
DOI : 10.1007/978-3-319-07130-5

J. Li, L. Deng, R. Haeb-umbach, and Y. Gong, Robust Automatic Speech Recognition ? A Bridge to Practical Applications, 2015.

B. Lee, M. Hasegawa-johnson, C. Goudeseune, S. Kamdar, S. Borys et al., AVICAR: audio-visual speech corpus in a car environment, Proc. Interspeech, pp.2489-2492, 2004.

S. Renals, T. Hain, and H. Bourlard, Interpretation of Multiparty Meetings the AMI and Amida Projects, 2008 Hands-Free Speech Communication and Microphone Arrays, pp.115-118, 2008.
DOI : 10.1109/HSCMA.2008.4538700

A. Stupakov, E. Hanusa, D. Vijaywargi, D. Fox, and J. Bilmes, The design and collection of COSINE, a multi-microphone in situ speech corpus recorded in noisy environments, Computer Speech & Language, vol.26, issue.1, pp.52-66, 2011.
DOI : 10.1016/j.csl.2010.12.003

C. Fox, Y. Liu, E. Zwyssig, and T. Hain, The Sheffield wargames corpus, Proc. Interspeech, pp.1116-1120, 2013.

J. Barker, R. Marxer, E. Vincent, and S. Watanabe, The third ???CHiME??? speech separation and recognition challenge: Dataset, task and baselines, 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), pp.504-511, 2015.
DOI : 10.1109/ASRU.2015.7404837

URL : https://hal.archives-ouvertes.fr/hal-01211376

M. P. Cooke, J. R. Hershey, and S. J. Rennie, Monaural speech separation and recognition challenge, Computer Speech & Language, vol.24, issue.1, pp.1-15, 2010.
DOI : 10.1016/j.csl.2009.02.006

URL : https://hal.archives-ouvertes.fr/hal-00598185

H. Hirsch and D. Pearce, The Aurora experimental framework for the performance evaluation of speech recognition systems under noisy conditions, Proc. ASR2000, pp.181-188, 2000.

Y. Lei, L. Burget, L. Ferrer, M. Graciarena, and N. Scheffer, Towards noise-robust speaker recognition using probabilistic linear discriminant analysis, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4253-4256, 2012.
DOI : 10.1109/ICASSP.2012.6288858

I. Peer, B. Rafaely, and Y. Zigel, Reverberation matching for speaker recognition, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.4829-4832, 2008.
DOI : 10.1109/ICASSP.2008.4518738

E. Vincent, S. Araki, and P. Bofill, The 2008 Signal Separation Evaluation Campaign: A Community-Based Approach to Large-Scale Evaluation, Proc. ICA, pp.734-741, 2009.
DOI : 10.1109/TASL.2007.899176

URL : https://hal.archives-ouvertes.fr/inria-00544168

A. El-solh, A. A. Cuhadar, and R. A. Goubran, Evaluation of Speech Enhancement Techniques for Speaker Identification in Noisy Environments, Ninth IEEE International Symposium on Multimedia Workshops (ISMW 2007), pp.235-239, 2007.
DOI : 10.1109/ISM.Workshops.2007.47

S. O. Sadjadi and J. H. Hansen, Assessment of single-channel speech enhancement techniques for speaker identification under mismatched conditions, Proc. Interspeech, pp.2138-2141, 2010.

]. 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, Proc. LREC, 2000.

C. Hanilci, T. Kinnunen, R. Saeidi, J. Pohjalainen, P. Alku et al., Comparing spectrum estimators in speaker verification under additive noise degradation, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4769-4772
DOI : 10.1109/ICASSP.2012.6288985

D. Martinez, L. Burget, T. Stafylakis, Y. Lei, P. Kenny et al., Unscented transform for ivector-based noisy speaker recognition, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4042-4046, 2014.
DOI : 10.1109/ICASSP.2014.6854361

S. Sarkar and K. S. Rao, Stochastic feature compensation methods for speaker verification in noisy environments, Applied Soft Computing, vol.19, pp.198-214, 2014.
DOI : 10.1016/j.asoc.2014.02.016

W. B. Kheder, D. Matrouf, J. Bonastre, M. Ajili, and P. Bousquet, Additive noise compensation in the i-vector space for speaker recognition, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4190-4194, 2015.
DOI : 10.1109/ICASSP.2015.7178760

Y. Hu and P. C. Loizou, Subjective comparison and evaluation of speech enhancement algorithms, Speech Communication, vol.49, issue.7-8, pp.588-601, 2007.
DOI : 10.1016/j.specom.2006.12.006

Y. Lei, M. Mclaren, L. Ferrer, and N. Scheffer, Simplified VTS-based I-vector extraction in noise-robust speaker recognition, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4065-4069, 2014.
DOI : 10.1109/ICASSP.2014.6854360

W. B. Kheder, D. Matrouf, P. Bousquet, J. Bonastre, and M. Ajili, Robust Speaker Recognition Using MAP Estimation of Additive Noise in i-vectors Space, Proc. SLSP, pp.97-107, 2014.
DOI : 10.1007/978-3-319-11397-5_7

H. Hirsch, Aurora-5 experimental framework for the performance evaluation of speech recognition in case of a handsfree speech input in noisy environments, Niederrhein Univ. of Applied Sciences, 2007.

Y. Lei, L. Burget, L. Ferrer, M. Graciarena, and N. Scheffer, A noise robust i-vector extractor using VTS for speaker recognition, Proc. ICASSP, pp.6788-6791, 2013.

C. Yu, G. Liu, S. Hahm, and J. Hansen, Uncertainty propagation in front end factor analysis for noise robust speaker recognition, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4017-4021, 2014.
DOI : 10.1109/ICASSP.2014.6854356

E. Vincent, J. Barker, S. Watanabe, J. Le-roux, F. Nesta et al., The second ‘chime’ speech separation and recognition challenge: Datasets, tasks and baselines, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.126-130, 2013.
DOI : 10.1109/ICASSP.2013.6637622

D. Ribas, E. Vincent, and J. R. Calvo, Full multicondition training for robust i-vector based speaker recognition, Proc. Interspeech, pp.1057-1061, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01158774

E. A. Habets, S. Gannot, and I. Cohen, Late Reverberant Spectral Variance Estimation Based on a Statistical Model, IEEE Signal Processing Letters, vol.16, issue.9, pp.770-773, 2009.
DOI : 10.1109/LSP.2009.2024791

C. F. Eyring, REVERBERATION TIME IN ???DEAD??? ROOMS, The Journal of the Acoustical Society of America, vol.1, issue.2A, pp.217-241, 1930.
DOI : 10.1121/1.1915175

M. Gardner, Factors affecting individual and group levels in verbal communication, Journal of the AES, vol.19, pp.560-569, 1971.

J. Eaton, N. D. Gaubitch, A. H. Moore, and P. A. Naylor, The ACE challenge — Corpus description and performance evaluation, 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp.1-5, 2015.
DOI : 10.1109/WASPAA.2015.7336912

T. Nishiura, M. Nakayama, Y. Denda, N. Kitaoka, K. Yamamoto et al., Evaluation framework for distant-talking speech recognition under reverberant environments: newest part of the CENSREC series, Proc. LREC, pp.1828-1834, 2008.

M. Jeub, M. Schäfer, and P. Vary, A binaural room impulse response database for the evaluation of dereverberation algorithms, 2009 16th International Conference on Digital Signal Processing, pp.1-5, 2009.
DOI : 10.1109/ICDSP.2009.5201259

L. Cristoforetti, M. Ravanelli, M. Omologo, A. Sosi, A. Abad et al., The DIRHA simulated corpus, Proc. LREC, pp.2629-2634, 2014.

N. Bertin, E. Camberlein, E. Vincent, R. Lebarbenchon, S. Peillon et al., A French corpus for distantmicrophone speech processing in real homes, Proc. Interspeech, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01343060

M. Lincoln, I. Mccowan, J. Vepa, and H. K. Maganti, The multi-channel Wall Street Journal audio visual corpus (MC-WSJ-AV): specification and initial experiments, IEEE Workshop on Automatic Speech Recognition and Understanding, 2005., pp.357-362, 2005.
DOI : 10.1109/ASRU.2005.1566470

H. Knecht, P. Nelson, G. Whitelaw, and L. Feth, Background Noise Levels and Reverberation Times in Unoccupied Classrooms, American Journal of Audiology, vol.11, issue.2, pp.65-71, 2002.
DOI : 10.1044/1059-0889(2002/009)

C. Crandell and F. Bess, Speech recognition of children in a typical classroom setting, American Speech-Language and Hearing Association, vol.29, pp.907-939, 1987.

T. Finitzo-hieber, Classroom acoustics, " in Auditory disorders in school children, pp.221-233, 1988.

K. S. Pearsons, R. L. Bennett, and S. Fidell, Speech levels in various noise environments, Office of Research and Development , Environmental Protection Agency, pp.1-77, 1977.

E. Van-heusden, R. Plomp, and L. C. Pols, Effect of ambient noise on the vocal output and the preferred listening level of conversational speech, Applied Acoustics, vol.12, issue.1, pp.31-43, 1979.
DOI : 10.1016/0003-682X(79)90037-9

J. Thiemann, N. Ito, and E. Vincent, The Diverse Environments Multi-channel Acoustic Noise Database (DEMAND): A database of multichannel environmental noise recordings, Proc. 21st Int. Congress on Acoustics, pp.1-6, 2013.
DOI : 10.1121/1.4799597

URL : https://hal.archives-ouvertes.fr/hal-00796707

H. H. Lazarus50-]-j, A. Hansen, W. Sangwan, and . Kim, Prediction of Verbal Communication is Noise??? A review: Part 1, Forensic Speaker Recognition: Law Enforcement and Counter-Terrorism, pp.439-464, 1986.
DOI : 10.1016/0003-682X(86)90039-3

J. H. Hansen, Analysis and compensation of speech under stress and noise for environmental robustness in speech recognition, Speech Communication, vol.20, issue.1-2, pp.151-173, 1996.
DOI : 10.1016/S0167-6393(96)00050-7

J. H. Hansen and V. Varadarajan, Analysis and Compensation of Lombard Speech Across Noise Type and Levels With Application to In-Set/Out-of-Set Speaker Recognition, IEEE Transactions on Audio, Speech, and Language Processing, vol.17, issue.2, pp.366-378, 2009.
DOI : 10.1109/TASL.2008.2009019

J. Garofalo, D. Graff, D. Paul, and D. Pallett, CSR-I (WSJ0) Complete, 2007.

M. P. Cooke, J. Barker, S. P. Cunningham, and X. Shao, An audio-visual corpus for speech perception and automatic speech recognition, The Journal of the Acoustical Society of America, vol.120, issue.5, pp.2421-2424, 2006.
DOI : 10.1121/1.2229005