Neural machine translation and the evolution of the localisation sector: implications for training
O'Brien, SharonORCID: 0000-0003-4864-5986 and Rossetti, AlessandraORCID: 0000-0002-2162-9639
(2020)
Neural machine translation and the evolution of the localisation sector: implications for training.
Journal of Internationalization and Localization, 7
(1/2).
pp. 95-121.
ISSN 2032-6904
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.
This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:
Science Foundation Ireland through the SFI Research Centres Programme, cofunded under the European Regional Development Fund through Grant no. 13/RC/2106
ID Code:
25321
Deposited On:
06 Jan 2021 11:44 by
Sharon O'brien
. Last Modified 06 Jan 2021 11:44