Machine Translation (Chat GPT) of short story “The Yellow Wallpaper” by Charlotte Perkins Gilman into Urdu: Examining Challenges and Implications

Abstract

This research investigates the limitations and challenges of machine translation in literary text through a qualitative research of the Urdu translation of Charlotte Perkins Gilman's short narrative “The Yellow Wallpaper”. Translating chosen extracts from English to Urdu and determining syntactic, pragmatic, and cultural appropriateness was conducted using ChatGPT as the machine translation software. Analysis revealed several flaws, including literal translation issues, loss of narrative voice, gender inconsistencies, and difficulties in translating figurative language. To redress these limitations, human-corrected translations were produced, which were more faithful, natural, and congruent with the intended Skopos of the source text. Internalization and externalization strategies were also analyzed during the study and were found to be impermissible for ChatGPT in that it could not retain the psychological and cultural subtleties inherent in the original narrative. These results were corroborated by existing literature regarding the failure of MT systems in literary translation, especially when it comes to idiomatic language, authorial tone, and cultural depiction. The findings reiterate the ongoing need for human translators in literary fields, given that machine-translated outputs are still inadequate in capturing the semantic, stylistic, and affective richness of sophisticated literary texts.