EVALUATING TRANSLATION QUALITY IN SIMULTANEOUS AND MACHINE TRANSLATION

Abstract

Translation quality plays a crucial role in effective multilingual communication. With the increasing use of both simultaneous translation and machine translation in international business, education, diplomacy, and media, evaluating translation quality has become an important area of research. Simultaneous translation relies on human interpreters who translate spoken language in real time, while machine translation uses artificial intelligence and computational models to automatically convert text or speech between languages. Although both methods aim to facilitate communication across language barriers, they differ significantly in terms of accuracy, speed, contextual understanding, and adaptability. This paper examines the criteria used to evaluate translation quality in simultaneous and machine translation, highlighting their strengths, limitations, and the challenges involved in assessment.