All you wished DeepL could do : Post-editing (PE) as a Fundamental Competence in Translators Training

Abstract

In recent years, neural machine translation systems have achieved a quite reasonable quality of their output, depending on certain factors. As a trainer, we decided to use the post-editing process of machine translated texts as oportunity for didactics. Focusing on machine translation errors can be used as a way to improve command of both the mother tongue and the second language. This presentation delves into direct translation (DE–ES) of general economic texts published by general print media. The final aims are: - to identify and classify error tendencies - to transfer this knowledge to the students so they can improve their command of mother (active) and work language (passive) - to enhance translation quality and performance and, as a result, to achieve higher academic grades