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A tree sequence alignment-based tree-to-tree translation model (2008)
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| Venue: | In Proceedings of ACL |
| Citations: | 42 - 2 self |
BibTeX
@INPROCEEDINGS{Zhang08atree,
author = {Min Zhang and Hongfei Jiang and Aiti Aw and Haizhou Li and Chew Lim Tan and Sheng Li},
title = {A tree sequence alignment-based tree-to-tree translation model},
booktitle = {In Proceedings of ACL},
year = {2008}
}
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Abstract
This paper presents a translation model that is based on tree sequence alignment, where a tree sequence refers to a single sequence of subtrees that covers a phrase. The model leverages on the strengths of both phrase-based and linguistically syntax-based method. It automatically learns aligned tree sequence pairs with mapping probabilities from word-aligned biparsed parallel texts. Compared with previous models, it not only captures non-syntactic phrases and discontinuous phrases with linguistically structured features, but also supports multi-level structure reordering of tree typology with larger span. This gives our model stronger expressive power than other reported models. Experimental results on the NIST MT-2005 Chinese-English translation task show that our method statistically significantly outperforms the baseline systems. 1
