Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Learning dependency translation models as collections of finite-state head transducers
Computational Linguistics - Special issue on finite-state methods in NLP
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Stochastic inversion transduction grammars and bilingual parsing of parallel corpora
Computational Linguistics
PCFG models of linguistic tree representations
Computational Linguistics
A syntax-based statistical translation model
ACL '01 Proceedings of the 39th 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
Loosely tree-based alignment for machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Learning non-isomorphic tree mappings for machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
The Alignment Template Approach to Statistical Machine Translation
Computational Linguistics
A phrase-based, joint probability model for statistical machine translation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Statistical machine translation by parsing
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
A hierarchical phrase-based model for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Dependency treelet translation: syntactically informed phrasal SMT
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Clause restructuring for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Improving a statistical MT system with automatically learned rewrite patterns
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Compositions of extended top-down tree transducers
Information and Computation
Linguistically annotated BTG for statistical machine translation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Syntactic constraints on paraphrases extracted from parallel corpora
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Joint morphological-lexical language modeling for machine translation
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
SSST '08 Proceedings of the Second Workshop on Syntax and Structure in Statistical Translation
Re-structuring, re-labeling, and re-aligning for syntax-based machine translation
Computational Linguistics
Learning to transform and select elementary trees for improved syntax-based machine translations
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Modality and negation in simt use of modality and negation in semantically-informed syntactic mt
Computational Linguistics
Re-training monolingual parser bilingually for syntactic SMT
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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We identify problems with the Penn Tree-bank that render it imperfect for syntax-based machine translation and propose methods of relabeling the syntax trees to improve translation quality. We develop a system incorporating a handful of relabeling strategies that yields a statistically significant improvement of 2.3 BLEU points over a baseline syntax-based system.