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EMNLP
2009

Better Synchronous Binarization for Machine Translation

8 years 10 months ago
Better Synchronous Binarization for Machine Translation
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.
Tong Xiao, Mu Li, Dongdong Zhang, Jingbo Zhu, Ming
Added 17 Feb 2011
Updated 17 Feb 2011
Type Journal
Year 2009
Where EMNLP
Authors Tong Xiao, Mu Li, Dongdong Zhang, Jingbo Zhu, Ming Zhou
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