Towards acquiring post-editing abilities through research- informed practical tasks

Abstract

The integration of machine translation (MT) in professional workflows, facilitated by recent gains in quality achieved by neural MT systems, means that translators are increasingly required to do post-editing (PE) in addition to their more traditional tasks. PE requires skills that are similar to, but also different from those expected of translators working without MT and revisors of human translation. This paper takes a minimalist view of the PE skill set, describing it in terms of three interrelated abilities – to identify errors, to distinguish between necessary and unnecessary edits, and to implement the edits appropriately – and examining it in the context of translator training. An experimental study is conducted with translation students untrained in PE who are asked to post-edit a text in conditions involving two variables: time pressure and source text access. The observed gaps in their skill set are taken as a starting point to develop ideas for the creation of practical PE tasks to be used in training. The paper may be of interest to translator educators looking to diversify their PE classes, whether in dedicated PE courses/modules or as part of other courses.

Keywords

• post-editing, machine translation, error identification, translator training, post-editing skill set