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

Du, Jinhua orcid logoORCID: 0000-0002-3267-4881, Way, Andy orcid logoORCID: 0000-0001-5736-5930, Qui, Zhengwei, Wasala, Asanka and Schäler, Reinhard (2015) Domain adaptation for social localisation-based SMT: a Case study using the Trommons platform. In: MT Summit Workshop on Post-Editing Technology and Practice (WPTP4) as part of Machine Translation Summit XV, 3 Oct-3 Nov, 2015, Miami, FL, USA.

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.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Published in: O'Brien, Sharon and Simard, Michel, (eds.) Proceedings of 4th Workshop on Post-Editing Technology and Practice (WPTP4). . Association for Machine Translation in the Americas (AMTA).
Publisher:Association for Machine Translation in the Americas (AMTA)
Official URL:https://amtaweb.org/wp-content/uploads/2015/10/MTS...
Copyright Information:© 2015 The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland through the ADAPT Centre (Grant 13/RC/2106) at Dublin City University, Grant 610879 for the Falcon project funded by the European Commission.
ID Code:23228
Deposited On:02 May 2019 08:33 by Thomas Murtagh . Last Modified 28 Aug 2020 13:25
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