Post-editing of English to Russian machine translation: Issues, methods, and optimization

Abstract

The aim of the study is to develop recommendations for optimizing English to Russian machine translation of scientific texts in the field of natural sciences during the post-editing stage, focusing on enhancing the quality of machine translation. The article provides a systematic categorization of post-editing methods for machine translation from English to Russian of texts in the field of natural sciences, specifically neurobiology, and conducts a multi-faceted analysis of the post-editing process of machine translation. This indicates the scientific novelty of the research. Successful post-editing examples are presented, discussing its prospects for improving machine translation systems. The results revealed that during post-editing, challenges arise as online services generate incorrect syntactic structures or introduce terminological units which meanings differ from those in the original language. An important task for the post-editor is to enhance the text's comprehension, which can be achieved, for instance, through sentence reconstruction.