One of the main challenges in crisis translation relates to a central dilemma: the need for both quality and productivity. In disasters and crises, it is paramount that highly sensitive content be translated accurately. However, in high-pressure situations, the sheer volume of texts and frequency of updates can adversely affect quality, and the lack of language professionals poses an additional challenge.

In light of the challenges that arise in different crisis phases and the current use of language technologies, this doctoral project explores the vital but often overlooked role of technology-supported translation practices in cascading crises with the aim of facilitating the work of professional and citizen translators. More specifically, it investigates the integration of speech synthesis into existing crisis translation workflows that make use of machine translation post-editing (PEMT). The underlying research hypothesis is that the use of speech synthesis will have a positive effect on the quality of the post-edited output and the translators’ productivity. The findings of this research will form the basis of guidelines for professional practice.

The project will use a mixed-methods approach, i.e., semi-structured interviews, questionnaires and an experimental study, to: