. Eronen, Antti Eronen Musical instrument recognition using ICA-based transform of features and discriminatively trained HMMs, 7th International Symposium on Signal Processing and Its Applications, 2003.

F. Et-ungvary, ]. B. Feiten, and T. Ungvary, Organization of sounds with neural nets, 1991.

F. Et-rossing, ]. N. Fletcher, and T. Rossing, The Physics of Musical Instruments, 1991.

F. Fraser, Anglea Fraser et Ichiro Fujinaga Toward real-time recognition of acoustic musical instruments, International Computer Music Conference, 1999.

M. Fujinaga, K. Fujinaga, and . Macmillan, Realtime recognition of orchestral instruments, International Computer Music Conference, 2000.

R. Gillet, G. Gillet, and . Richard, Automatic transcription of drum loops, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004.
DOI : 10.1109/ICASSP.2004.1326815

. Goto, Rwc music database : Music genre database and musical instrument sound database, 4th International Conference on Music Information Retrieval, pp.229-230, 2003.

. Goto, RWC music database : Popular, classical, and jazz music databases, International Conference on Music Information Retrieval (ISMIR), 2002.

]. K. Grey, Multidimensional perceptual scaling of musical timbres, The Journal of the Acoustical Society of America, vol.61, issue.5, pp.1270-1277, 1977.
DOI : 10.1121/1.381428

]. I. Bibliographie-[-guyon-et-elisseeff, . Guyon, and . Elisseeff, An introduction to feature and variable selection, Journal of Machine Learning Research, vol.3, pp.1157-1182, 2003.

. Guyon, Gene selection for cancer classification using support vector machines, Machine Learning, vol.46, issue.1/3, pp.389-422, 2002.
DOI : 10.1023/A:1012487302797

T. Hastie, R. Hastie, and . Tibshirani, Classification by pairwise coupling, Advances in Neural Information Processing Systems, 1998.
DOI : 10.1214/aos/1028144844

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

. Herrera, Automatic Classification of Musical Instrument Sounds, Journal of New Music Research, vol.32, issue.1, pp.3-21, 2003.
DOI : 10.1076/jnmr.

/. Iso and . Iec, MPEG-2 Advanced Audio Coding, AAC. International Standard ISO, 1997.

/. Iso and . Iec, Information technology -multimedia content description interface -part 4 : Audio, International Standard ISO/IEC FDIS 15938-4 :2001(E), ISO/IEC, 2001.

T. Joachims and . Joachims, Svm light support vector machine

I. Kaminskyj, Multi-feature musical instrument sound classifier, 2000.

M. Kaminskyj, A. Kaminskyj, and . Materka, Enhanced automatic source identification of monophonic musical instrument sounds, 1996 Australian New Zealand Conference on Intelligent Information Systems. Proceedings. ANZIIS 96, pp.189-194, 1995.
DOI : 10.1109/ANZIIS.1996.573893

M. Kashino, H. Kashino, and . Mursae, A sound source identification system for ensemble music based on template adaptation and music stream extraction, Speech Communication, vol.27, issue.3-4, pp.337-349, 1998.
DOI : 10.1016/S0167-6393(98)00078-8

]. B. Kedem, Spectral analysis and discrimination by zero-crossings, Proceedings of the IEEE, pp.1477-1493, 1986.
DOI : 10.1109/PROC.1986.13663

]. R. Kendall, The Role of Acoustic Signal Partitions in Listener Categorization of Musical Phrases, Music Perception: An Interdisciplinary Journal, vol.4, issue.2, pp.185-214, 1986.
DOI : 10.2307/40285360

. Kinoshita, Musical sound source identification based on frequency component adaptation, IJCAI Workshop on Computational Auditory Scene Analysis (IJCAI-CASA), 1999.

. Kitahara, Category-level identification of non-registered musical instrument sounds, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004.
DOI : 10.1109/ICASSP.2004.1326811

. Kitahara, Musical instrument identification based on f0-dependent multivariate normal distribution, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2003.

]. A. Klapuri, Sound onset detection by applying psychoacoustic knowledge, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999.
DOI : 10.1109/ICASSP.1999.757494

J. Kohavi, G. Kohavi, and . John, Wrappers for feature subset selection, Artificial Intelligence, vol.97, issue.1-2, pp.273-324, 1997.
DOI : 10.1016/S0004-3702(97)00043-X

C. Kostek, A. Kostek, and . Czyzewski, Automatic recognition of musical instrument sounds -further developments. Dans 110th AES convention, The Netherlands, 2001.

K. Et-czyzewski, ]. B. Kostek, and A. Czyzewski, Representing musical instrument sounds for their automatic classification, J. Audio Eng. Soc, vol.9, pp.768-785, 2001.

K. Et-sreenivas, ]. A. Krishna, and T. V. Sreenivas, Music instrument recognition : from isolated notes to solo phrases, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.265-268, 2004.

F. De, 106 VI.8. Résultats de classification avec l'approche de sélection binaire, comparéscomparésà ceux obtenus avec l'approche classique avec d = 20, VI.7. Performances des différentes sélections comparéescomparéesà celles, p.110