Preserving Personality through a Pivot Language Low-Resource NMT of Ancient Languages

We investigate the effectiveness of neural machine translation in a low-resource setting, where particular attention is given to preserving the rhetorical style of a given persona. In particular, we attempt to complete Cicero’s translation of Timaeus, a text originally written by Plato in Attic Greek. Due to the scarcity of parallel Attic Greek and Classical Latin text, we use English as a pivot language. Finally, we explore how additional texts, which may help improve the accuracy of the model, affect the preservation of a particular persona (i.e. Socrates) through translation into the pivot language and subsequently the target language.