Machine and Human Translation: A Review

Abstract

This literature review studies the comparative efficiency and trials of machine translation (MT) versus human translation (HT). The rapid development of artificial intelligence (AI) and natural language processing has led to considerable assistance in accessing MT, making them viable options for many translation tasks. Nonetheless, in the face of these technological advancements, HT continues to be quintessential, especially for nuanced, context-rich texts. The motive here is to look into the strengths and weaknesses of both approaches, drawing from recent studies, user experiences, and expert analyses. This review focuses on the accuracy, speed, cost, and contextual understanding and interpretability of MT and HT. This highlights how MT is superior in terms of speed and cost efficiency, while HT is superior in terms of cultural and traditional nuances, idiomatic expressions and contextual accuracy. A hybrid model that combines MT and HT to leverage the strengths of both is also taken into account here, suggesting that a synergistic approach may be the future of translation. This comprehensive analysis aims to provide insights for researchers, translators, and organizations seeking to optimize their translation practices.