THEORETICAL FOUNDATIONS OF LINGUOPRAGMATIC POST-EDITING IN ARTIFICIAL INTELLIGENCE-BASED TRANSLATION
Keywords:
Keywords: artificial intelligence, neural machine translation, post-editing, linguopragmatics, pragmatic equivalence, translation quality.Abstract
Artificial intelligence (AI) has become one of the most influential technologies in contemporary translation practice. Neural machine translation systems are capable of generating grammatically correct and semantically coherent target texts within a short period of time. Nevertheless, AI-generated translations frequently fail to preserve pragmatic meaning, communicative intention, discourse coherence, and culture-specific elements. These shortcomings reduce translation quality and necessitate human intervention through post-editing. Among different post-editing approaches, linguopragmatic post-editing occupies a special place because it aims not only to eliminate linguistic errors but also to restore the communicative value of the original text. The present study examines the theoretical foundations of linguopragmatic post-editing in artificial intelligence-based translation. It discusses the concepts of linguopragmatics, pragmatic equivalence, communicative intention, speech acts, implicature, and presupposition, as well as their role in improving AI-generated translations. The paper also analyzes the theoretical principles that underlie linguopragmatic post-editing and highlights their significance for contemporary translation studies.
