Abstract
Binarization of Synchronous Context Free Grammars (SCFG) is essential for achieving polynomial time complexity of decoding for SCFG parsing based machine translation systems. In this paper, we first investigate the excess edge competition issue caused by a leftheavy binary SCFG derived with the method of Zhang et al. (2006). Then we propose a new binarization method to mitigate the problem by exploring other alternative equivalent binary SCFGs. We present an algorithm that iteratively improves the resulting binary SCFG, and empirically show that our method can improve a string-to-tree statistical machine translations system based on the synchronous binarization method in Zhang et al. (2006) on the NIST machine translation evaluation tasks. © 2009 ACL and AFNLP.
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CITATION STYLE
Xiao, T., Li, M., Zhang, D., Zhu, J., & Zhou, M. (2009). Better synchronous binarization for machine translation. In EMNLP 2009 - Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: A Meeting of SIGDAT, a Special Interest Group of ACL, Held in Conjunction with ACL-IJCNLP 2009 (pp. 362–370). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1699510.1699558
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