A Comparative Analysis of Cognitive and AI Approaches in English-Indonesian Translation: Manual vs. Automated Methods
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Ines Nur Irawan
This study used a qualitative approach to explore cognitive and AI-driven methods of English-Indonesian translation, focusing on comparing manual and automated processes. It investigated how human translators managed comprehension, reformulation, and production and evaluated the performance of AI tools like Google Neural Machine Translation (GNMT). The study examined vital factors such as linguistic accuracy, cultural adaptation, and handling of idiomatic expressions using qualitative expert reviews. Structural differences between English and Indonesian were highlighted, revealing common translation challenges. The findings showed that while AI systems offered quick translations, human translators provided greater cultural insight and precision. Ultimately, the research suggested that a hybrid model, combining both human and AI methods, would produce the best results, particularly for complex texts.
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