Machine Translation, Post-Editing, and Quality Assessment in English–Romanian Medical Translation: Insights from Professional Practice

Abstract

The integration of machine translation (MT) and artificial intelligence into translation workflows has significantly transformed professional practice, particularly in high-stakes domains such as medical translation. This study investigates professional translators’ perspectives on post-editing (PE) and translation quality assessment (TQA) in English–Romanian medical translation. Drawing on structured interviews and thematic analysis, the findings indicate that MT is primarily used as a support tool due to persistent issues related to terminology and contextual accuracy. Post-editing is considered essential, though often applied without structured adherence to standards such as ISO 18587, while TQA models are unevenly implemented in practice. The study also identifies a significant gap between academic training and professional requirements, particularly regarding technological and domain-specific competences. These findings highlight the need for a more integrated and practice-oriented approach to translator training in the Romanian context.