A non-contiguous Tree Sequence Alignment-based Model for Statistical Machine Translation

The tree sequence based translation model allows the violation of syntactic boundaries in a rule to capture non-syntactic phrases, where a tree sequence is a contiguous sequence of subtrees. This paper goes further to present a translation model based on non-contiguous tree sequence alignment, where a non-contiguous tree sequence is a sequence of sub-trees and gaps. Compared with the contiguous tree sequencebased model, the proposed model can well handle non-contiguous phrases with any large gaps by means of non-contiguous tree sequence alignment. An algorithm targeting the noncontiguous constituent decoding is also proposed. Experimental results on the NIST MT-05 Chinese-English translation task show that the proposed model statistically significantly outperforms the baseline systems.

• Type: Journal
• Year: 2009
• Where: ACL
• Authors: Jun Sun, Min Zhang, Chew Lim Tan
• Keywords: ACL 2009, Computational Linguistics, Non-contiguous Tree Sequence, Tree Sequence, Tree Sequence Alignment