Type

Conference Proceedings

Authors

Andy Way
Josef van Genabith
Declan Groves
Karolina Owczarzak
Bart Mellebeek

Subjects

Linguistics

Topics
target language skeleton machine translating algorithm lexical selection english source language statistical machine translation

A syntactic skeleton for statistical machine translation (2006)

Abstract We present a method for improving statistical machine translation performance by using linguistically motivated syntactic information. Our algorithm recursively decomposes source language sentences into syntactically simpler and shorter chunks, and recomposes their translation to form target language sentences. This improves both the word order and lexical selection of the translation. We report statistically significant relative improvementsof 3.3% BLEU score in an experiment (English!Spanish) carried out on an 800-sentence test set extracted from the Europarl corpus.
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, Josef van Genabith, Declan Groves, Karolina Owczarzak, Bart Mellebeek

Experts in our system

1
Andy Way
Dublin City University
Total Publications: 229
 
2
Josef van Genabith
Dublin City University
Total Publications: 115