Journal Article


Andy Way
Maite Aragonés Lumeras



machine translation productivity machine translating human critical component skills complementarity

On the complementarity between human translators and machine translation (2017)

Abstract Many translators are fearful of the impact of Machine Translation (MT) on their profession, broadly speaking, and on their livelihoods more specifically. We contend that their concern is misplaced, as human translators have a range of skills, many of which are currently – with no signs of any imminent breakthroughs on the horizon – impossible to replicate by automatic means. Nonetheless, in this paper, we will show that MT engines have considerable potential to improve translators’ productivity and ensure that the output translations are more consistent. Furthermore, we will investigate what machines are good at, where they break down, and why the human is likely to remain the most critical component in the translation pipeline for many years to come
Collections Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: ADAPT
Ireland -> Dublin City University -> Publication Type = Article
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating

Full list of authors on original publication

Andy Way, Maite Aragonés Lumeras

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Andy Way
Dublin City University
Total Publications: 229