On multiple context-free grammars
Theoretical Computer Science
Foundations of statistical natural language processing
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The Theory of Parsing, Translation, and Compiling
The Theory of Parsing, Translation, and Compiling
Practical experiments with regular approximation of context-free languages
Computational Linguistics - Special issue on finite-state methods in NLP
Finite-state transducers in language and speech processing
Computational Linguistics
The use of shared forests in tree adjoining grammar parsing
EACL '93 Proceedings of the sixth conference on European chapter of the Association for Computational Linguistics
The recognition capacity of local syntactic constraints
EACL '91 Proceedings of the fifth conference on European chapter of the Association for Computational Linguistics
Precise n-gram probabilities from stochastic context-free grammars
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Introduction to probabilistic automata (Computer science and applied mathematics)
Introduction to probabilistic automata (Computer science and applied mathematics)
Cross-entropy and estimation of probabilistic context-free grammars
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Probabilistic Context-Free Grammars Estimated from Infinite Distributions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computation of distances for regular and context-free probabilistic languages
Theoretical Computer Science
Variational decoding for statistical machine translation
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
Intersection for weighted formalisms
FSMNLP '11 Proceedings of the 9th International Workshop on Finite State Methods and Natural Language Processing
A practical algorithm for intersecting weighted context-free grammars with finite-state automata
FSMNLP '11 Proceedings of the 9th International Workshop on Finite State Methods and Natural Language Processing
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We show that under certain conditions, a language model can be trained on the basis of a second language model. The main instance of the technique trains a finite automaton on the basis of a probabilistic context-free grammar, such that the Kullback-Leibler distance between grammar and trained automaton is provably minimal. This is a substantial generalization of an existing algorithm to train an n-gram model on the basis of a probabilistic context-free grammar.