Reviving functionalism: Applying translation-oriented text analysis to synthetic text (editing)

This paper investigates the potential application of translation-relevant text analysis. Rooted in the functionalist approach and Skopos theory, the translation-relevant text analysis is seen as instrumental in translation education for assessing the quality of synthetic text output for translation purposes (MT and/or AI) and improving (post-)editing performance relating to said output. Despite recent advancements in machine translation and the partially self-professed potential of AI models, accurately conveying the intended function of the target text remains a challenge in professional translation practices. This paper argues that salvaging functionalist theory can benefit both translator education and, ultimately, professional translation practices. To support this argument, three use cases are presented in which the key principles of functionalism and Skopos theory are applied to develop critical text analysis skills necessary for handling and editing synthetic text. Keywords: Functionalism, Translation Technology, Machine Translation, Generative Artificial Intelligence, Post-editing