Summary
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.
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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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101153456 |
| Start date: | 01-06-2025 |
| End date: | 31-05-2027 |
| Total budget - Public funding: | - 199 440,00 Euro |
Cordis data
Original description
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.
Status
SIGNEDCall topic
HORIZON-MSCA-2023-PF-01-01Update Date
03-01-2025
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