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Translators’ perceptions of literary post-editing using statistical and neural machine translation

Moorkens, Joss ORCID: 0000-0003-4864-5986, Toral, Antonio ORCID: 0000-0003-2357-2960, Castilho, Sheila ORCID: 0000-0002-8416-6555 and Way, Andy ORCID: 0000-0001-5736-5930 (2018) Translators’ perceptions of literary post-editing using statistical and neural machine translation. Translation Spaces, 7 (2). pp. 240-262. ISSN 2211-3711

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Abstract

In the context of recent improvements in the quality of machine translation (MT) output and new use cases being found for that output, this article reports on an experiment using statistical and neural MT systems to translate literature. Six professional translators with experience of literary translation produced English-to-Catalan translations under three conditions: translation from scratch, neural MT post-editing, and statistical MT post-editing. They provided feedback before and after the translation via questionnaires and interviews. While all participants prefer to translate from scratch, mostly due to the freedom to be creative without the constraints of segment-level segmentation, those with less experience find the MT suggestions useful.

Item Type:Article (Published)
Refereed:Yes
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:John Benjamin's Publishing
Official URL:http://dx.doi.org/10.1075/ts.18014.moo
Copyright Information:© 2018 John Benjamin's Publishing
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:23898
Deposited On:01 Nov 2019 15:32 by Thomas Murtagh . Last Modified 20 Jan 2021 16:53

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