Abstract: Novel Journal of Applied Sciences Research

Abstract:
With the rapid advancement of artificial intelligence (AI) and natural language processing (NLP) technologies, machine translation (MT) has made significant progress in terms of efficiency and accuracy. However, MT continues to face numerous challenges in understanding linguistic context, addressing cultural differences, and handling complex semantic transformations. In contrast, human translation (HT) exhibits unique advantages in managing ambiguity, metaphor, and emotional expression. This paper explores the similarities and differences in the cognitive mechanisms involved in MT and HT during the translation process. By comparing the performance of MT and HT in various translation tasks and integrating theories from cognitive science, this study analyzes cognitive load, decision-making mechanisms, and information processing patterns inherent in translation. The goal is to uncover the limitations and potential of MT and to investigate the possibilities of collaboration between MT and HT in the future.