A. Denis, A. Denis, M. Quinard, and G. Pitel, A Deep-Parsing Approach to Natural Language Understanding in Dialogue System : Results of a Corpus- Based Evaluation, A Natural Language System for Spoken Language Applications, Computational Linguistics, pp.61-86, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00112897

A. Levin, E. Levin, and R. Pieraccini, Concept-Based Spontaneous Speech Understanding System, and Lefevre F., A 2+1-Level Stochastic Understanding Model , Automatic Speech Recognition and Understanding workshop, pp.555-558, 1995.

A. Charniak, E. Charniak, C. Hendrickson, N. Jacobson, M. Perkowitz et al., Décodage conceptuel et apprentissage automatique : application au corpus de dialogue Homme-Machine ME, Equations for Partof-Speech Tagging 11th National Conference on Artificial IntelligenceMEDIA, 2005] Bonneau-Maynard H. and Rosset S. and, pp.784-789, 1993.

C. Ayache, A. Kuhn, D. Mostefa, H. Bonneau-maynard, C. Ayache et al., Semantic annotation of the French Media dialog corpus, Proceedings of the European Conference on Speech Communication and Technology Lisboa Portugal. [MEDIA Results of French Evalda-Media evaluation campaign for litteral understanding, pp.2054-2059, 2005.

R. , B. Raymond, C. Béchet, F. , D. Mori et al., On the use of finite state transducers for semantic interpretation, Speech Communication, vol.48, pp.3-4, 2006.
URL : https://hal.archives-ouvertes.fr/hal-01314627

A. Mohri, M. Mohri, F. Pereira, and M. Riley, Weighted finite-state transducers in speech recognition, Computer Speech & Language, vol.16, issue.1, pp.69-88, 2002.
DOI : 10.1006/csla.2001.0184