Issues in Machine Translation with reference to the Story “Thakur ka kuan” by Munshi Premchand

This paper explores the issues encountered in machine translation, specifically using Google Translate, in translating Munshi Premchand's short story Thakur Ka Kuan ("Thakur's Well"). The study identifies key challenges, including the misinterpretation of cultural references, idiomatic expressions, and contextual meaning that are integral to Premchand's narrative style. Machine translation often produces literal translations that lack the nuance and emotional depth present in the original text, leading to misrepresentation of the story’s themes. For instance, socio-cultural terms and metaphors central to the story's message are frequently mistranslated or omitted entirely. The translation also struggles with maintaining consistency in tense and sentence structure, further diluting the narrative. This paper argues that while machine translation offers convenience for basic translations, it remains insufficient for complex literary works, where cultural, emotional, and contextual understanding is crucial. A comparative analysis with a human-translated version highlights these deficiencies and suggests that human input remains essential for accurate literary translations. The findings underscore the need for improved machine learning models to address these linguistic and cultural intricacies.