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The Ghost in the Translation Machine: Charting Language Proficiency, Exploring Technology, and Making Translators Fit for a Digital Age

Project description

Innovations in translator training

All EU communication should be multilingual. The surge in digital content and cross-border interactions underscores the need for proficient translation services. However, traditional methods struggle to keep pace with the volume and complexity of modern linguistic demands. The European Commission’s vision of a digitally adept Europe further amplifies the urgency for innovative solutions in language education and translation technology. Supported by the Marie Skłodowska-Curie Actions (MSCA) programme, the LinguaTech project pioneers a comprehensive study. It aims to redefine translator training by integrating advanced language skills with technologies like neural machine translation and AI post-editing. LinguaTech will equip translators with expertise to thrive in a fast evolving language industry, bolstering Europe’s competitive edge on the global stage.

Objective

The EU’s commitment to support its multilingual character, the European Commission’s priority of creating ‘a Europe fit for the Digital Age’ and the raising EU and global demand for translation services, as evidenced, e.g. by the latest European translation industry ELIS reports (2013-2021), entails research and investment in language training on the one hand, and the provision of high-quality translation services that seize the opportunities offered by the latest technologies on the other hand.
LinguaTech is the first in-depth study that produces and combines on new findings on additional language (AL) competence at the highest levels, alongside neural machine translation and Generative AI post-editing competences, and applies these to translator training. It will result in a definition and measure (descriptors) of the AL competence of translators that will be supplemented with insight into the linguistic demands of machine translation post-editing and selected Generative AI models. They will feed into the ultimate deliverable, the LinguaTech Toolbox, complete with descriptors, guidelines (how to teach AL to translators in the AI age), tools (linguistic match-up marker), and a short online training course on technology-enabled AL teaching. AL teaching, streamlined with the demands of newest technology, will give translation students a competitive advantage upon their entry on the EU language market in terms of expertise, cost, quality, technology, and adaptability to innovation, while at the same time it will provide a better skilled workforce for the quickly growing language industry and institutional language departments. Additionally, the insight generated by LinguaTech and its dissemination and exploitation will benefit experienced translators, who frequently face insecurity towards technology. The research will be supported by a secondment at RWS, who are major player on the global and European translation market, and will be available open source.

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2023-PF-01

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Coordinator

UNIVERSITAT WIEN
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 199 440,96
Address
UNIVERSITATSRING 1
1010 WIEN
Austria

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Region
Ostösterreich Wien Wien
Activity type
Higher or Secondary Education Establishments
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Total cost

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