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ACL
2009

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

10 years 9 months ago
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.
Jun Sun, Min Zhang, Chew Lim Tan
Added 16 Feb 2011
Updated 16 Feb 2011
Type Journal
Year 2009
Where ACL
Authors Jun Sun, Min Zhang, Chew Lim Tan
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