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.
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