Chiang 2005
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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
This paper describes a statistical phrase-based machine 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.
