A study on machine translation tools: A comparative error analysis between DeepL and Yandex for Russian-Italian medical translation

The present research is aimed at conducting a study on Russian-Italian medical translation with regard to the current development of two Machine Translation tools that feature prominently in today’s Neural Machine Translation framework, namely DeepL and Yandex. For the purpose of our research, we have selected three highly specialized and three popular-science articles concerning coronavirus pandemic. Such a choice is justified by the willingness not only to analyse recently published scientific documents but also to investigate the particular linguistic implications of 2020’s coronavirus pandemic outbreak, which has introduced in every-day communication a whole set of terms whose use was previously limited to the language of science, as well as coined a group of new terms, which entered the boundaries of scientific terminology. We have considered this existing linguistic phenomenon as a proper condition to test the performances of Machine Translation tools. In particular, we discuss the most relevant features of the comparative error analysis as well as the BLEU metric for both DeepL and Yandex.