Article published in:
Translation Spaces
Vol. 7:2 (2018) ► pp. 240–262

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

| Dublin City University
| University of Groningen
| Dublin City University
| Dublin City University
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.
Keywords: machine translation, literary machine translation, neural machine translation, human factors in machine translation
Published online: 28 November 2018
https://doi.org/10.1075/ts.18014.moo
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