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

Joss Moorkens*, Antonio Toral, Sheila Castilho, Andy Way

*Bijbehorende auteur voor dit werk

    OnderzoeksoutputAcademicpeer review

    16 Citaten (Scopus)


    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.

    Originele taal-2English
    Pagina's (van-tot)240-262
    Aantal pagina's23
    TijdschriftTranslation Spaces
    Nummer van het tijdschrift2
    StatusPublished - 28-nov-2018

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