Le projet OPTIMICE : une optimisation de la qualité des traductions de métadonnées par la collaboration entre acteurs du monde scientifique et traduction automatique

Abstract

The OPTIMICE project, which stands for optimising machine translation of metadata and its integration into the editorial chain, aims at devising a method – transferrable to other journals and disciplinary fields – that combines neural machine translation (DeepL) and human post-editing to improve the quality of article metadata (abstracts, keywords, etc.) from French to English in the editorial process of journals. A team of translation researchers who are also translators worked on four journals edited by the Presses universitaires de Rennes (PUR), in collaboration with the editorial comittees and the MSHB (Maison des sciences de l’Homme en Bretagne). The translation of the paper metadata by their authors and by machine translation was comparatively assessed. A survey on translation practices among researchers in HSS was led, and recommendations for writing and translating metadata were formulated for the organized integration of the methodology within the editorial process.

Keywords

• nmt (neural machine translation)
• post-editing
• hss
• metadata
• journal
• tan (traduction automatique neuronale)
• post-édition
• shs
• métadonnées
• revues
• [shs]humanities and social sciences