Machine vs. human translation of cultural dimensions in children’s literature : Andersen and Rowling as Cases of Study /

Abstract

This comparative study investigates the efficacy of Machine Translation (MT) in translating children’s literature, specifically examining its treatment of cultural references. The selected genres for analysis are fantasy fiction and fairy tales fiction. Accordingly, the study includes short stories by Hans Christian Andersen alongside the third book in the Harry Potter series, Harry Potter and the Prisoner of Azkaban, by J. K. Rowling. By employing a comparative and contrastive approach, the MT output, generated by ChatGPT, is analyzed against human translations. The findings offer valuable insights into the effectiveness of MT in preserving cultural identity in children's literature. The results reveal that while ChatGPT tends to produce literal translations with minimal cultural filtering, human translators employ adaptive strategies such as omission, substitution, and compensation to maintain cultural relevance. The study concludes that although MT tools are rapidly advancing, they still require human oversight to handle culturally sensitive content, particularly in texts intended for young audiences. This research ends with practical recommendations for translators, NLP engineers, and future scholars to enhance culturally aware MT systems in the Arab context. Keywords: Machine Translation, Children’s Literature, Cultural Appropriation, Fantasy, Fairy