Skip to Main content Skip to Navigation
Conference papers

Post-édition statistique pour l'adaptation aux domaines de spécialité en traduction automatique

Abstract : Statistical Post-Editing of Machine Translation for Domain Adaptation This paper presents a statistical approach to adapt generic machine translation systems to the medical domain through an unsupervised post-edition step. A statistical post-edition model is built on statistical machine translation outputs aligned with their translation references. Evaluations carried out to translate medical texts from French to English show that a generic machine translation system can be adapted a posteriori to a specific domain. Two systems are studied : a state-of-the-art phrase-based implementation and an online publicly available software. Our experiments also indicate that selecting sentences for post-edition leads to significant improvements of translation quality and that more gains are still possible with respect to an oracle measure.
Document type :
Conference papers
Complete list of metadata

Cited literature [19 references]  Display  Hide  Download
Contributor : bibliothèque Universitaire Déposants HAL-Avignon Connect in order to contact the contributor
Submitted on : Wednesday, February 27, 2019 - 10:04:10 AM
Last modification on : Tuesday, January 14, 2020 - 10:38:06 AM
Long-term archiving on: : Tuesday, May 28, 2019 - 1:19:41 PM


Files produced by the author(s)


  • HAL Id : hal-01320234, version 1



Raphael Rubino, Stéphane Huet, Fabrice Lefèvre, Georges Linares. Post-édition statistique pour l'adaptation aux domaines de spécialité en traduction automatique. 19ème conférence sur le Traitement Automatique des Langues Naturelles (TALN), Jun 2012, Grenoble, France. pp.527-534. ⟨hal-01320234⟩



Record views


Files downloads