Teaching Machine Translation on a Translation MA: Some Recommendations Regarding Course Content

Machine translation has developed to a phenomenal degree even over the quarter century that has passed since the appearance of the Babel Fish tool, and needless to say, university curricula have had to keep up with this rapid pace of change. Based on two courses taught as part of the MA in Translation and Bilingual Communication at Hong Kong Baptist University, the twelve recommendations presented in this article take students from their likely existing knowledge of free online machine translation systems and bring them to the stage when they are able to create and train their own engine. Along the way, topics such as the integration of machine translation into translation memory tools, the post-editing of machine translation output, the use of interactive adaptive machine translation, the deployment of corpus-based analysis to detect machine translation errors, and the acquisition and exploitation of bilingual parallel text help to ensure that students receive a broad, detailed and relatively innovative introduction to the topic. The
paper argues that, taken together, these components equip our students to start engaging with machine translation-based methodologies in their professional activity.