Paper: Syntax-Based Alignment: Supervised Or Unsupervised?

ACL ID C04-1060
Title Syntax-Based Alignment: Supervised Or Unsupervised?
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2004
Authors

Tree-based approaches to alignment model translation as a sequence of probabilistic op- erations transforming the syntactic parse tree of a sentence in one language into that of the other. The trees may be learned directly from parallel corpora (Wu, 1997), or provided by a parser trained on hand-annotated treebanks (Ya- mada and Knight, 2001). In this paper, we compare these approaches on Chinese-English and French-English datasets, and find that au- tomatically derived trees result in better agree- ment with human-annotated word-level align- ments for unseen test data.