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Article published In:
Fair MT: Towards ethical, sustainable Machine Translation
Edited by Joss Moorkens, Dorothy Kenny and Félix do Carmo
[Translation Spaces 9:1] 2020
► pp. 123–149

Machine translation, ethics and the literary translator’s voice

ORCID logo | Dublin City University
ORCID logo | Heriot-Watt University

Recent work in translation studies has established the literary translator’s voice as an ethical concern, but there has been little empirical research so far into how the translator’s voice is affected in workflows involving machine translation. In this article, we investigate how the use of neural machine translation influences the textual voice (Alvstad et al. 2017) of renowned translator from English into German, Hans-Christian Oeser. Based on an experiment in which Oeser post-edits an excerpt from a novel he had previously translated, we show how his textual voice is somewhat diminished in his post-edited work compared to its stronger manifestation in his translation work. At the same time Oeser’s contextual voice (ibid.) remains strong in his comments on the text he produces in post-editing mode. The article is offered as a methodological intervention and represents an initial attempt to design studies in literary machine translation that put the focus on human translators, allowing their voices to be heard more clearly than has previously been the case.

Keywords: literary translation, translator’s voice, textual voice, contextual voice, translator style, neural machine translation
Article outline
  • Introduction
  • Voice and its ethical import in translation
  • Textual and contextual voice
  • The translator’s voice in recent approaches to themachine translation of literature
  • Towards more ecologically valid approaches to the study of literary translators at work
  • Research design
    • Participant
    • Experiment set up
    • Research questions
    • Research materials
    • Procedure
  • Analysis
  • Conclusion
  • Acknowledgements
  • Notes
  • References
Published online: 17 August 2020
DOI logo
https://doi.org/10.1075/ts.00024.ken
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