A statistical approach to machine translation
Computational Linguistics
Text speech translation by means of subsequential transducers
Extended finite state models of language
Journal of the ACM (JACM)
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
Learning dependency translation models as collections of finite-state head transducers
Computational Linguistics - Special issue on finite-state methods in NLP
An optimal tabular parsing algorithm
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Word re-ordering and DP-based search in statistical machine translation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Finding structural correspondences from bilingual parsed corpus for corpus-based translation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Acquisition of phrase-level bilingual correspondence using dependency structure
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Efficient parsing for bilexical context-free grammars and head automaton grammars
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
A finite-state approach to machine translation
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
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Existing studies show that a weighted context-free transduction of reasonable quality can be effectively learned from examples. This paper investigates the approximation of such transduction by means of weighted rational transduction. The advantage is increased processing speed, which benefits real-time applications involving spoken language.