Abstract
Systems based on synchronous grammars and tree transducers promise to improve the quality of statistical machine translation output, but are often very computationally intensive. The complexity is exponential in the size of individual grammar rules due to arbitrary re-orderings between the two languages, and rules extracted from parallel corpora can be quite large. We devise a linear-time algorithm for factoring syntactic re-orderings by binarizing synchronous rules when possible and show that the resulting rule set significantly improves the speed and accuracy of a state-of-the-art syntax-based machine translation system. © 2006 Association for Computational Linguistics.
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CITATION STYLE
Zhang, H., Huang, L., Gildea, D., & Knight, K. (2006). Synchronous binarization for machine translation. In HLT-NAACL 2006 - Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings of the Main Conference (pp. 256–263). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1220835.1220868
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