Difference between revisions of "Chiang 2005"

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== Summary ==
 
== Summary ==
  
A statistical phrase-based translation model that uses hierarchical phrases — phrases that contain subphrases. The model is formally a [[UsesMethod::synchronous context-free grammar|Synchronous Context-Free Grammars]] but is learned from a bitext without any syntactic information. Using BLEU as a metric, the hierarchical phrase based model achieves a relative improvement of 7.5% over Pharaoh, a state-of-the-art phrase-based system.
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A statistical phrase-based translation model that uses hierarchical phrases — phrases that contain subphrases. The model is formally a [[UsesMethod::Synchronous Context-Free Grammars|synchronous context-free grammar]] but is learned from a bitext without any syntactic information. Using BLEU as a metric, the hierarchical phrase based model achieves a relative improvement of 7.5% over Pharaoh, a state-of-the-art phrase-based system.
  
 
== Experimental results ==
 
== Experimental results ==
  
 
== Related papers ==
 
== Related papers ==

Revision as of 09:59, 1 November 2011

Citation

Chiang, D. 2005. A Hierarchical Phrase-Based Model for Statistical Machine Translation. In Proceedings of the 43rd Annual Meeting of the ACL, pp. 263–270, Ann Arbor. Association for Computational Linguistics.

Online version

Information Sciences Institute, University of Southern California

Summary

A statistical phrase-based translation model that uses hierarchical phrases — phrases that contain subphrases. The model is formally a synchronous context-free grammar but is learned from a bitext without any syntactic information. Using BLEU as a metric, the hierarchical phrase based model achieves a relative improvement of 7.5% over Pharaoh, a state-of-the-art phrase-based system.

Experimental results

Related papers