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.