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Automatic determination of a stochastic bi-gram class language model,e have developed a class-based bigram model determined entirely automatically from written text corpora. The classes are not defined, the words are not tagged, the solely assumption is the number of classes..We get a robust model which insures a more complete coverage of the succession probabilities

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尾巴

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Application of OSTIA to machine translation tasks,defined from a conceptually constrained task which was recently proposed within the field of Cognitive Science. Large corpora of English-to-Spanish and English-to-German translations have been generated, and exhaustive experiments have been carried out to test the ability of OSTIA to learn these tra

溃烂

Inducing probabilistic grammars by Bayesian model merging, grammar; subsequently, elements of the model (such as states or nonterminals) are . to achieve generalization and a more compact representation. The choice of what to merge and when to stop is governed by the Bayesian posterior probability of the grammar given the data, which formalizes a trade-off

unstable-angina

Statistical estimation of Stochastic Context-Free Grammars using the Inside-Outside algorithm and ad for the estimation of the rule probabilities of Stochastic Context-Free Grammars with the same time complexity as the Inside-Outside algorithm. The transformation algorithm relates Stochastic Context-Free Grammars, whose characteristic grammar is proper and does not have single rules, to Stochasti

装饰

溺爱

expire

Forming grammars for structured documents: an application of grammatical inference,les. The examples consist of structures of individual documents, and they can be collected either by converting typographical tagging of documents prepared for printing into structural tags, or by using document recognition techniques. Our method forms first finite-state automata describing the exam

厌食症

A comparison of syntactic and statistical techniques for off-line OCR, test is to show that syntactic methods can perform as robustly as purely statistical techniques on noisy data. The main result is that, even given a very simplistic and idiosyncratic input coding, the syntactic method performs slightly better than any of the other methods. Furthermore, it is likely