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Abstract
This article explores the comparative strengths and weaknesses of machine translation and human translation. With the rise of neural machine translation systems such as Google Translate and Deepl, questions have emerged about whether machines can replace human translators. Drawing on scholarly perspectives from Hutchins, Koehn, Venuti, Pym, Garcia, Basnett, and Baker, this study examines machine translation and human translation across dimensions of speed, cost, accuracy, cultural adaptation, and stylistic quality. Examples of idiomatic expressions, technical documents, and literary texts illustrate the practical implications of each approach. The findings suggest that while machine translation offers efficiency and accessibility, human translation remains indispensable for nuanced, culturally sensitive, and stylistically complex texts. The article concludes that a hybrid model, combining machine translation tools with human expertise, represents the most effective solution for contemporary translation practices.
References
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