Statistical machine translation in the translation curriculum: overcoming obstacles and empowering translators

In this paper we argue that the time is ripe for translator educators to engage with Statistical Machine Translation (SMT) in more profound ways than they have done to date. We explain the basic principles of SMT and reflect on the role of humans in SMT workflows. Against a background of diverging opinions on the latter, we argue for a holistic approach to the integration of SMT into translator training programmes, one that empowers rather than marginalises translators. We discuss potential barriers to the use of SMT by translators generally and in translator training in particular, and propose some solutions to problems thus identified. More specifically, cloud-based services are proposed as a means of overcoming some of the technical and ethical challenges posed by more advanced uses of SMT in the classroom. Ultimately the paper aims to pave the way for the design and implementation of a new translator-oriented SMT syllabus at our own University and elsewhere.