A Comparative Study of Human and Machine Translation in English and Urdu Language: Evaluating Accuracy Using Google Translate and ChatGPT

Abstract

It has been observed that the difference between human and machine translation in English–Urdu texts creates several challenges in producing accurate and natural translations. Machine translation tools are widely used, but they often fail to handle cultural expressions, idioms, and narrative flow. A number of studies are available on machine translation, but limited research is available to explore a detailed comparison between human and machine translation in English - urdu text types. Thereby applying qualitative methodology and using Skopos Theory, Dynamic Equivalence, and Error Analysis, the current study aims to compare the translations of narrative texts, figurative idioms, and formal informational passages. The study highlighted that machine translation performs well in simple informational sentences, but human translation provides more natural, culturally appropriate, and meaningful results. Providing clear comparison and analysis can be an effective way to understand the limitations of machine translation and the important role of human translators.