Pangeanic in the EXPERT Project (EXPloiting Empirical appRoaches to Translation)

1. Pangeanic in the EXPERT Project (EXPloiting Empirical appRoaches to Translation) Manuel HERRANZ, Alex HELLE, Elia YUSTE, Ruslan MITKOV, Lucia SPECIA m.herranz / a.helle / e.yuste @ pangeanic.com, R.Mitkov@wlv.ac.uk, l.specia@dcs.shef.ac.uk • Introduction • EU-funded, 48-month R&D project that involves the development of next generation translation-related technologies to address the needs of both translators and the EC multilingualism policy. • Consortium: • Research Group in Computational Linguistics, University of Wolverhampton, UK (coordinator) • Pangeanic, Spain • Universidad de Málaga, Spain • University of Sheffield, UK • Universitaet des Saarlandes, Germany • Translated srl, Italy • Dublin City University, Ireland • Hermes Traducciones y ServiciosLingüísticos, SL, Spain • Universiteit van Amsterdam, Netherlands • Method • EXPERT will build an Initial Training Network and encompass these Research Projects: • EXPERT Training Objectives to be achieved through a network-wide training programme consisting of: • Winter School on Scientific & Technological Training (M13) • Complementary Skills Training event (M19) • Scientific & Technological Workshop (M28) • Business Showcase (M43) • Results • To address five main research sub-topics: User perspective; Data collection and preparation; Improve matching and retrieval with linguistic processing; Hybrid approaches for translation; Human translator in the loop: Informing users and learning from user feedback • Resulting training materials on core research areas and complementary skills to be created specifically for EXPERT and shared with the rest of the community. • Tools developed by the ERs in the last year of the project to be presented at the Business Showcase – opportunity to disseminate project outcomes to potential end-users: translators & general public. • Focus on the innovation of resulting tools • Training on both those new tools and skills of the trade (e.g. post-editing) • Pangeanic’s Expertise & Involvement • Pangeanic, a forward-looking translation agency, also a provider of MT customization solutions, to act as industry technology partner in EXPERT. • Pangeanic to give unlimited access to its entire computing infrastructure and resources, including our massive data repositories and statistical language models, DIY platform, automated retraining features, etc. • Like other partners, Pangeanic to contribute to different project stages by (co-)hosting/supervising a number of post-graduate and post-doctoral researchers. • Focus on: • implementation and evaluation of the new hybrid computer-aided translation technology • investigation of translators’ requirements from translation technologies • confidence estimation of corpus-based approaches to translation • Participation to Winter School, supporting DCU in the 3-hour tutorial Hybrid Solutions for Translation. • Co-organize Training Workshop with DCU and lead Complementary Skills Training 3-hr tutorial Project Management (supported by USAAR) and 3-hr Publication Strategies (supported by UoW). • Next steps • Present and collect expert feedback about project objectives, methodology, etc. in conferences, e.g. MT Summit . • Prepare and finalise contents for EXPERT Winter School • For more information, check out the project website: http://expert-itn.eu/ • Aim • To train young researchers, namely Early Stage Researchers (ESRs) and Experienced Researchers (ERs), to promote the research, development and use of hybrid language translation technologies. • To date, MT tools not designed to aid professional translators. Shortcomings: user-unfriendly interfaces, lack of awareness of translator's feedback, etc. • TM systems also perform poorly for texts that have not been translated before. • No clear boundaries – both technologies meant to help humans to produce high quality, reliable, fast and cheap translations.  EXPERT to accommodate requirements of both user types: professional translators and readers of translations Acknowledgements The research project has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2007-2013<tel:2007-2013>/ under REA grant agreement n°[317471]. The authors would also like to thank the rest of the project consortium members for their collaboration.