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
The Alignment Template Approach to Statistical Machine Translation
Computational Linguistics
A hierarchical phrase-based model for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Hierarchical Phrase-Based Translation
Computational Linguistics
Rule filtering by pattern for efficient hierarchical translation
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Online large-margin training of syntactic and structural translation features
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
SSST '08 Proceedings of the Second Workshop on Syntax and Structure in Statistical Translation
Syntax augmented machine translation via chart parsing
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
A joint rule selection model for hierarchical phrase-based translation
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Discriminative word alignment with a function word reordering model
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Hierarchical phrase-based translation with weighted finite-state transducers and shallow-n grammars
Computational Linguistics
Soft dependency constraints for reordering in hierarchical phrase-based translation
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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Hierarchical phrase-based models are attractive because they provide a consistent framework within which to characterize both local and long-distance reorderings, but they also make it difficult to distinguish many implausible reorderings from those that are linguistically plausible. Rather than appealing to annotation-driven syntactic modeling, we address this problem by observing the influential role of function words in determining syntactic structure, and introducing soft constraints on function word relationships as part of a standard log-linear hierarchical phrase-based model. Experimentation on Chinese-English and Arabic-English translation demonstrates that the approach yields significant gains in performance.