A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
A polynomial-time algorithm for statistical machine translation
ACL '96 Proceedings of the 34th annual meeting on Association for 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
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
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
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
Head-Driven Statistical Models for Natural Language Parsing
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
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Syntax augmented machine translation via chart parsing
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Effective use of linguistic and contextual information for statistical machine translation
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Maximum entropy based phrase reordering for hierarchical phrase-based translation
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
A word-class approach to labeling PSCFG rules for machine translation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Learning hierarchical translation structure with linguistic annotations
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
A novel dependency-to-string model for statistical machine translation
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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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Chiang's hierarchical phrase-based (HPB) translation model advances the state-of-the-art in statistical machine translation by expanding conventional phrases to hierarchical phrases -- phrases that contain sub-phrases. However, the original HPB model is prone to over-generation due to lack of linguistic knowledge: the grammar may suggest more derivations than appropriate, many of which may lead to ungrammatical translations. On the other hand, limitations of glue grammar rules in the original HPB model may actually prevent systems from considering some reasonable derivations. This paper presents a simple but effective translation model, called the Head-Driven HPB (HD-HPB) model, which incorporates head information in translation rules to better capture syntax-driven information in a derivation. In addition, unlike the original glue rules, the HD-HPB model allows improved reordering between any two neighboring non-terminals to explore a larger reordering search space. An extensive set of experiments on Chinese-English translation on four NIST MT test sets, using both a small and a large training set, show that our HD-HPB model consistently and statistically significantly outperforms Chiang's model as well as a source side SAMT-style model.