New Dilemmas in Corpus-Based Translation Studies

The corpus-linguistic approach in translation studies, which gained prominence in the discipline with the study of translation universals (Baker 1995), became one of the most significant and prolific research paradigms of recent decades, largely thanks to technological advances and increasingly sophisticated research tools. This development laid the foundations for corpus-based translation studies. At the same time, the growing professionalization of the field and the digitalization of the translation industry have transformed not only the translation process and the role of the translator (Eszenyi et al.2023, Massey et al.2023) but also the linguistic characteristics of translated texts (Daems et al. 2018, De Clercq et al. 2021). The augmented translation environment – characterized by the widespread use of CAT tools and the rapidly improving performance of neural machine translation (NMT) and generative AI – raises the question of whether it is still appropriate to speak of translation, translators, transfer operations, and translation universals in the traditional sense or new definitions are needed. Against this backdrop, the present paper explores how the project-based approach, the digital transformation and growing automation have affected the translation process and translated discourse, while also considering the past, present, and future challenges of corpus construction, corpus design, and corpus-based translation research.