K. N. Stevens, Toward a model for lexical access based on acoustic landmarks and distinctive features, The Journal of the Acoustical Society of America, vol.111, issue.4, pp.1872-1891, 2002.
DOI : 10.1121/1.1458026

A. Juneja, Speech recognition based on phonetic features and acoustic landmarks, 2004.

J. R. Glass, A probabilistic framework for segment-based speech recognition, Computer Speech & Language, vol.17, issue.2-3, pp.137-152, 2003.
DOI : 10.1016/S0885-2308(03)00006-8

T. N. Sainath, Island-driven search using broad phonetic classes, 2009 IEEE Workshop on Automatic Speech Recognition & Understanding, pp.287-292, 2009.
DOI : 10.1109/ASRU.2009.5373547

M. Hasegawa-johnson, J. Baker, S. Borys, K. Chen, E. Coogan et al., Landmark-based speech recognition: report of the, Proc. of ICASSP'05, pp.213-216, 2004.

G. Gravier and D. Moraru, Towards Phonetically-Driven Hidden Markov Models: Can We Incorporate Phonetic Landmarks in HMM-Based ASR?, Proc. of NOLISP'07, pp.161-168, 2007.
DOI : 10.1007/978-3-540-77347-4_13

R. André-obrecht, A new statistical approach for the automatic segmentation of continuous speech signals, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol.36, issue.1, pp.29-40, 1988.
DOI : 10.1109/29.1486

M. Hall, Correlation-based feature selection for machine learning, 1999.

M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann et al., The WEKA data mining software, ACM SIGKDD Explorations Newsletter, vol.11, issue.1, pp.10-18, 2009.
DOI : 10.1145/1656274.1656278

B. Mathieu, S. Essid, T. Fillon, J. Prado, and G. Richard, YAAFE, an easy to use and efficient audio feature extraction software, Proc. of ISMIR-2010, 2010.

K. Sjlander, The snack sound toolkit, " www.speech.kth.se/snack, 2004.

S. Galliano, G. Gravier, and L. Chaubard, The ESTER 2 evaluation campaign for the rich transcription of French broadcasts, Proc. of INTERSPEECH, pp.1149-1152, 2009.