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Abstract: We propose a new Mgorithm which allows for the identification of any stochastic deterministic regular language as well as the determination of the probabilities of the strings in the language. The algorithm builds the prefix tree acceptor from the sample set and merges systematically equivaJent states. Experimentally, it proves very fast a.ad the time needed grows only linearly with the size of the sample set. (Update)
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BibTeX entry: (Update)
R. C. Carrasco and J. Oncina. Learning stochastic regular grammars by means of a state merging method. In The 2nd Intl. Collo. on Grammatical Inference and Applications, pages 139--152, 1994. http://citeseer.ist.psu.edu/carrasco94learning.html More
@inproceedings{ carrasco94learning,
author = "R. Carrasco and J. Oncina",
title = "Learning stochastic regular grammars by means of a state merging method",
booktitle = "Proc. 2nd International Colloquium on Grammatical Inference - {ICGI} '94",
volume = "862",
publisher = "Springer-Verlag",
pages = "139--150",
year = "1994",
url = "citeseer.ist.psu.edu/carrasco94learning.html" }
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1 NeumI Computation (context) - Giles, Extracting et al. - 1992
1 Kuhn: Induction of Finite-state Languages Using Second-Order.. (context) - Wartons - 1992
1 Vidal: Simulation of Stochastic Regular Grammars through Sim.. (context) - Castafio, Casacuberta - 1993
1 Omohundro: Hidden Markov Model Induction by B (context) - Stolcke - 1993
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