Exploring Syntactic Structural Features for Sub-Tree Alignment Using Bilingual Tree Kernels

We propose Bilingual Tree Kernels (BTKs) to capture the structural similarities across a pair of syntactic translational equivalences and apply BTKs to sub-tree alignment along with some plain features. Our study reveals that the structural features embedded in a bilingual parse tree pair are very effective for sub-tree alignment and the bilingual tree kernels can well capture such features. The experimental results show that our approach achieves a significant improvement on both gold standard tree bank and automatically parsed tree pairs against a heuristic similarity based method. We further apply the sub-tree alignment in machine translation with two methods. It is suggested that the subtree alignment benefits both phrase and syntax based systems by relaxing the constraint of the word alignment.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Jun Sun, Min Zhang, Chew Lim Tan
• Keywords: ACL 2010, Bilingual Tree Kernels, Computational Linguistics, Sub-tree Alignment, Tree