The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Discriminative training and maximum entropy models for statistical machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Learning syntactic patterns using boosting and other classifier combination schemas
TSD'05 Proceedings of the 8th international conference on Text, Speech and Dialogue
TSD'05 Proceedings of the 8th international conference on Text, Speech and Dialogue
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We present an approach for machine translation by applying the GenPar toolkit on POS-tagged and syntactically parsed texts Our experiment in Hungarian-English machine translation is an attempt to develop prototypes of a syntax-driven machine translation system and to examine the effects of various preprocessing steps (POS-tagging, lemmatization and syntactic parsing) on system performance The annotated monolingual texts needed for different language specific tasks were taken from the Szeged Treebank and the Penn Treebank The parallel sentences were collected from the Hunglish Corpus Each developed prototype runs fully automatically and new Hungarian-related functions are built in The results are evaluated with BLEU score.