Type

Conference Proceedings

Authors

Andy Way
Mary Hearne
Ventsislav Zhechev
John Tinsley

Subjects

Linguistics

Topics
machine translation example based mt state of the art machine translating language tree alignment data oriented translation approaches

Robust language pair-independent sub-tree alignment (2007)

Abstract Data-driven approaches to machine translation (MT) achieve state-of-the-art results. Many syntax-aware approaches, such as Example-Based MT and Data-Oriented Translation, make use of tree pairs aligned at sub-sentential level. Obtaining sub-sentential alignments manually is time-consuming and error-prone, and requires expert knowledge of both source and target languages. We propose a novel, language pair-independent algorithm which automatically induces alignments between phrase-structure trees. We evaluate the alignments themselves against a manually aligned gold standard, and perform an extrinsic evaluation by using the aligned data to train and test a DOT system. Our results show that translation accuracy is comparable to that of the same translation system trained on manually aligned data, and coverage improves.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: National Centre for Language Technology (NCLT)
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres

Full list of authors on original publication

Andy Way, Mary Hearne, Ventsislav Zhechev, John Tinsley

Experts in our system

1
Andy Way
Dublin City University
Total Publications: 229
 
2
John Tinsley
Dublin City University
Total Publications: 13