Developing User-centred Approaches to Technological Innovation in Literary Translation

Start date
Sept. 1, 2022
End date
Aug. 31, 2024
European Union (Marie Skłodowska-Curie Action)

About DUAL-T

Recent years have seen a growing research interest on the application of translation technology to literary translation workflows, mostly in the form of Machine Translation (MT) or post-editing of MT output. In these studies, literary translators' voices are virtually absent. This project will address the discrepancy between research in Computer Science/AI and Translation Studies, as well as the absence of literary translators from the conversation surrounding technological innovation in their profession. It will do so by proactively integrating literary translators' input in the co-creation of a new technology-inclusive workflow. Professional literary translators will be asked to perform literary translation tasks using (1) a word processor, (2) a Computer-Aided Translation (CAT) tool environment, (3) a Machine Translation Post-editing platform. User testing will be performed using keystroke logging and screen capturing. In-depth interviews and focus groups will be conducted before and after the translation task to register changes in participants' attitudes towards technology before and after using it, as well as advantages and pain points of the tool employed. Being the first study of this kind in literary translation, results will help to (1) devise a technology-inclusive literary translation workflow employing a user-led approach, (2) assess whether and to what extent translation technology can enhance literary translators (particularly, the potential of CAT tools to work in combination with MT and/or as an alternative to MT-centric approaches will be assessed), and (3) mediate a dialogue between literary translators and translation technology developers by feeding back data on literary translators' use of and attitudes towards translation technology to the project's industry partner. It is expected that the project's findings will also contribute to the wider conversation around Human-Computer Interaction in other professions.