Automatic Cross-Lingual Similarization of Dependency Grammars for Tree-based Machine Translation

Wenbin Jiang1, Wen Zhang1, Jinan Xu2, Rangjia Cai3
1Institute of Computing Technology, CAS, 2Beijing Jiaotong University, 3Qinghai Normal University


Abstract

Structural isomorphism between languages benefits the performance of cross-lingual applications. We propose an automatic algorithm for cross-lingual similarization of dependency grammars, which automatically learns grammars with high cross-lingual similarity. The algorithm similarizes the annotation styles of the dependency grammars for two languages in the level of classification decisions, and gradually improves the cross-lingual similarity without losing linguistic knowledge resorting to iterative cross-lingual cooperative learning. The dependency grammars given by cross-lingual similarization have much higher cross-lingual similarity while maintaining non-triviality. As applications, the cross-lingually similarized grammars significantly improve the performance of dependency tree-based machine translation.