Abstract
Probabilistic Context-Free Grammars can be used for speech recognition or syntactic analysis thanks to especially efficient algorithms. In this paper, we propose an instantiation of such a grammar, which mathematical properties are intuitively more suitable for those tasks than SCFG’s (Stochastic CFG), without requiring specific analysis algorithms. Results on the Susanne text show that up to 33% of analysis errors made by a SCFG can be avoided with this model.
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References
Adam Berger. Convexity, maximum likelihood and all that.
J.-C. Chappelier and M. Rajman. A generalized CYK algorithm for parsing stochastic CFG. In Proc. of 1st Workshop on Tabulation in Parsing and Deduction (TAPD’98), pp. 133–137, Paris (France), Apr 1998.
J.-C. Chappelier and M. Rajman. Grammaire à substitution d’arbre de complexité polynomiale: un cadre efficace pour dop. In Actes de la 8ème conférence sur le Traitement Automatique desd Langues Naturelles (TALN 2001), volume 1, pp. 133–142, 2001.
J.-C. Chappelier, M. Rajman, R. Aragüés, and A. Rozenknop. Lattice parsing for speech recognition. In Proc. of 6ème conférence sur le Traitement Automatique du Langage Naturel (TALN’ 99), pp. 95–104, Cargèse (France), Jul 1999.
Joshua T. Goodman. Parsing Inside-Out. Ph.D. thesis, Harvard University, Cambridge, Massachusetts, May 1998.
F. Jelinek, J. D. Lafferty, and R. L. Mercer. Basic methods of probabilistic context-free grammars. In P. Laface and R. De Mori, editors, Speech Recognition and Understanding: Recent Advances, Trends and Applications, volume 75 of F: Computer and System Science. Springer, 1992.
Mark Johnson. Pcfg models of linguistic tree representations. Computational Linguistics, 24(4):613–632, December 1998.
John Lafferty. Gibbs-Markov models. In Computing Science and Statistics, volume 27, pp. 370–377, 1996.
Stephen Della Pietra, Vincent J. Della Pietra, and John D. Lafferty. Inducing features of random fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(4):380–393, 1997.
Antoine Rozenknop and Marius-Calin Silaghi. Algorithme de décodage de treillis selon le critère du coût moyen pour la reconnaissance de la parole. In Actes de la 8ème conférence sur le Traitement Automatique des Langues Naturelles (TALN 2001), number 1, pp. 391–396, Tours, juillet 2001. Association pour le Traitement Automatique des Langues.
A. Stolcke. An efficient probabilistic context-free parsing algorithm that computes prefix probabilities. Computational Linguistics, 21(2):165–201, 1995.
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Rozenknop, A. (2002). Gibbsian Context-Free Grammar for Parsing. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2002. Lecture Notes in Computer Science(), vol 2448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46154-X_7
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DOI: https://doi.org/10.1007/3-540-46154-X_7
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