Type

Conference Proceedings

Authors

Andy Way
Qun Liu
Ergun Bicici

Subjects

Linguistics

Topics
machine translation systems computational linguistics training and development machine translating statistical machine translation feature decay algorithms information retrieval language pairs

Parallel FDA5 for fast deployment of accurate statistical machine translation systems (2014)

Abstract We use parallel FDA5, an efficiently parameterized and optimized parallel implementation of feature decay algorithms for fast deployment of accurate statistical machine translation systems, taking only about half a day for each translation direction. We build Parallel FDA5 Moses SMT systems for all language pairs in the WMT14 translation task and obtain SMT performance close to the top Moses systems with an average of $3.49$ BLEU points difference using significantly less resources for training and development.
Collections Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Computational linguistics
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres
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 -> Subject = Computer Science
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: Centre for Next Generation Localisation (CNGL)
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating
Ireland -> Dublin City University -> Subject = Computer Science: Information retrieval
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing

Full list of authors on original publication

Andy Way, Qun Liu, Ergun Bicici

Experts in our system

1
Andy Way
Dublin City University
Total Publications: 229
 
2
Qun Liu
Dublin City University
Total Publications: 31
 
3
Ergun Bicici
Dublin City University
Total Publications: 12