This semester, the module focuses on post-editing machine translation output in translation contexts. It trains second-year students to evaluate, correct, and improve automatically generated translations according to professional quality standards. Students develop skills in error identification, linguistic revision, and stylistic refinement while distinguishing between light and full post-editing. Emphasis is placed on accuracy, fluency, and informed decision-making. The course prepares learners to integrate post-editing practices within contemporary translation workflows.
- Teacher: Dalila MESLOUB