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Machine-Learning-based English Quranic Translation: An Evaluation of ChatGPT
Abstract
Translating the Holy Quran into different languages is a crucial task. It is a daunting one, given the linguistic complexity and rich cultural context of this holy scripture. The recent advancements in technology, especially in artificial intelligence, brought about a pressing need to explore the potential of machine learning-based tools in easing the translation of religious texts, the Holy Quran in particular. This study explores the potential of adopting ChatGPT, a large language model (LLM) powered by machine learning, in English Quranic translation. The study aims to assess the accuracy, adequacy, and cultural sensitivity of ChatGPT's English Quranic translation and identify potential challenges and limitations of using this tool in this domain. The study employed a comparative analysis approach, evaluating ChatGPT's translation of the El Fatiha Chapter against five human-generated translations using BLEU (Bilingual Evaluation Understudy) and METEOR (Metric for Evaluation of Translation with Explicit ORdering) machine translation metrics. The study also utilized an interpretation of the chapter by El Qurtubi to ensure that ChatGPT has the entire linguistic and cultural context of the chapter. The study's findings indicated that ChatGPT's English translation of El Fatiha achieved a moderate level of accuracy and adequacy with mean BLEU and METEOR scores of 0,48 and 0,78, respectively. However, there were areas where ChatGPT's translation could be improved. The use of ML-based tools such as ChatGPT in English Quranic translation offers promising benefits as it can aid translators in the translation process.
Article information
Journal
International Journal of Linguistics, Literature and Translation
Volume (Issue)
7 (8)
Pages
128-136
Published
Copyright
Copyright (c) 2024 Ismail Dahia, Mohammed Belbacha
Open access
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This work is licensed under a Creative Commons Attribution 4.0 International License.