Neural machine translation and the evolution of the localisation sector

Abstract

The localisation sector is highly technologized and evolves rapidly. Though significant consideration has been given to third-level training in localisation for Translation Studies students, the nature of the industry is such that this topic demands regular attention. Our objective was to survey employees and executive managers to understand what impact recent technological developments, including but not limited to neural machine translation (NMT), might have on future skills and training requirements for localisation linguists. Our findings are that linguists in localisation take up a variety of roles, including transcreation, data mining, project and vendor management. NMT is considered an important advancement, and its introduction has emphasised the need for a critical use of technology, while opening new career pathways, such as data curation and annotation. Domain specialisation is recommended for those who translate, and transferable soft skills are more essential than ever. Increased industry and interdisciplinary collaborations in training are also considered valuable.

The Language Engineer: A Transversal, Emerging Role for the Automation Age

“…In the language services sector, digital labour platforms affect translation processes substantially, from the lack of interaction between project managers and translators to not having enough time to study whether the conditions of a translation task are suitable for their profile for fear that someone else will accept the task more rapidly, or the moving from more stable labour relationships to a proliferation of freelancers and outsourcing (Moorkens & O'Brien, 2017;O'Brien & Rossetti, 2020;ELIS, 2022). Likewise, the proliferation of quality metrics and TQA scores are also key for these platforms, Quaderns de Filologia: Estudis Lingüístics XXVII: 17-48. doi: 10.7203/QF.27.24622 as there are systems that automatically block translators who do not reach a quality threshold, leaving them out of the pool of job offers.…”

Post-Editing as the Means to Activate Students’ Thinking and Analytical Process: Psycholinguistic Aspects

“…The arrival of next-generation MT software, including the one based on statistical and neural networks (Schmidhofer & Mair, 2019;O'Brien & Rossetti, 2020), made some authors (Pym, 2013) predict its eventual replacement of fully human translation in many spheres of activity. Thus, it is suggested (Pym, 2013;Mellinger, 2017) to incorporate MT in multiple courses across the curriculum (or, at least, the majority of translation-related disciplines), rather than concentrating the material in a stand-alone course or module, though there are some other opinions concerning this issue as well (Esqueda, 2021).…”