Conference Proceedings


Reinhard Schaler
Asanka Wasala
Zhengwei Qui
Andy Way
Jinhua Du


Computer Science

digital content non profit organisations community action statistical machine translation cross entropy machine translating domain adaptation social adaptation

Domain adaptation for social localisation-based SMT: a Case study using the Trommons platform (2015)

Abstract Social localisation is a kind of community action, which matches communities and the content they need, and supports their localisation efforts. The goal of social localisation-based statistical machine translation (SL-SMT) is to support and bridge global communities exchanging any type of digital content across different languages and cultures. Trommons is an open platform maintained by The Rosetta Foundation to connect non-profit translation projects and organisations with the skills and interests of volunteer translators, where they can translate, post-edit or proofread different types of documents. Using Trommons as the experimental platform, this paper focuses on domain adaptation techniques to augment SL-SMT to facilitate translators/post-editors. Specifically, the Cross Entropy Difference algorithm is used to adapt Europarl data to the social localisation data. Experimental results on English–Spanish show that the domain adaptation techniques can significantly improve translation performance by 6.82 absolute BLEU points and 5.99 absolute TER points compared to the baseline.
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 -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating

Full list of authors on original publication

Reinhard Schaler, Asanka Wasala, Zhengwei Qui, Andy Way, Jinhua Du

Experts in our system

Andy Way
Dublin City University
Total Publications: 229
Jinhua Du
Dublin City University
Total Publications: 38