Teaching machine translation : exchange of good practices

This paper presents a best-practice overview of how machine translation (MT) is taught and learned at the IUED Institute of Translation and Interpreting of the ZHAW University of Applied Sciences (Switzerland). By adopting a consultative perspective on the deployment of MT systems in organisations, the module in question introduces students to the core practices of pre-editing and post-editing, and to the basics of rule-based, statistical and neural MT. It highlights the strengths and weaknesses of using such systems and includes interactions with professional language technologists and language technology managers in order to equip students with the procedural knowledge of how to deploy such systems in organisation and to advise on their deployment