Computer-assisted literary translation applied to the historical novel (Ge Spanish): Training and comparison of machine translation systems

Computer-assisted literary translation (CALT) has become a research point of interest in the last decade. Youdale's work (2020) proves the usefulness of CAT tools for the literary translator; Kenny and Winters (2020) look into CAT impact on the translator's style; Moorkens et al. (2018) compare different machine translation (MT) systems and Toral & Way (2015) train a MT engine for translating novels. Based on these and on my prior study (Castillo, 2022a, 20221), 2017), in the present work, a MT system is trained with the existing translation of a German historical novel of legal content, to be applied to the translation of a second novel on the same topic. Subsequently, the machine translation is post-edited and its errors compared to the results of an untrained MT system, with special focus on post-editing style and legal language. The purpose is to ascertain to what extent a customized MT system can assist in the literary translator's complex work.