A systematic comparison of various statistical alignment models
Computational Linguistics
Stochastic inversion transduction grammars and bilingual parsing of parallel corpora
Computational Linguistics
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
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Is it harder to parse Chinese, or the Chinese Treebank?
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Maximum entropy based phrase reordering model for statistical machine translation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Further meta-evaluation of machine translation
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
Syntax augmented machine translation via chart parsing
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Complete search space exploration for SITG inside probability
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
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In this paper we propose a novel method for inferring an Inversion Transduction Grammar (ITG) from a bilingual parallel corpus with linguistic information from the source or target language. Our method combines bilingual ITG parse trees with monolingual linguistic trees in order to obtain a Syntax Augmented ITG (SAITG). The use of a modified bilingual parsing algorithm with bracketing information makes possible that each bilingual subtree has a correspondent subtree in the monolingual parsing. In addition, several binarization techniques have been tested for the resulting SAITG. In order to evaluate the effects of the use of SAITGs in Machine Translation tasks, we have used them in an ITG-based machine translation decoder. The results obtained using SAITGs with the decoder for the IWSLT-08 Chinese-English machine translation task produce significant improvements in BLEU.