Type

Conference Proceedings

Authors

Andy Way
Antonio Toral
Arefeh Kazemi

Subjects

Linguistics

Topics
wordnet statistical machine translation meaning phrase based statistical machine translation english language training data english to farsi machine translating

Using Wordnet to improve reordering in hierarchical phrase-based statistical machine translation (2016)

Abstract We propose the use of WordNet synsets in a syntax-based reordering model for hierarchical statistical machine translation (HPB-SMT) to enable the model to generalize to phrases not seen in the training data but that have equivalent meaning. We detail our methodology to incorporate synsets’ knowledge in the reordering model and evaluate the resulting WordNetenhanced SMT systems on the English-toFarsi language direction. The inclusion of synsets leads to the best BLEU score, outperforming the baseline (standard HPBSMT) by 0.6 points absolute.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: ADAPT
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: Centre for Next Generation Localisation (CNGL)
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating

Full list of authors on original publication

Andy Way, Antonio Toral, Arefeh Kazemi

Experts in our system

1
Andy Way
Dublin City University
Total Publications: 229
 
2
Antonio Toral
Dublin City University
Total Publications: 18