Assessing the Quality of Hidden Proverbs Translation in the Holy Qur’ān: Human vs. Artificial Intelligence English Translations

Document Type : Original Research

Authors

1 Department of English Language, Imam Reza International University, Mashhad, Iran

2 Department of English Language, Baqir Al-Olum University, Qom, Iran

Abstract

Linguistic issues are important in the textual analysis of translated texts. Among the most sensitive and significant texts translated into different languages, the Holy Qur’ān stands out. The text and texture of the Qur’ān are so unique that one cannot easily understand it without prior knowledge of its linguistic and extralinguistic aspects. One of the most challenging linguistic issues in the Qur’ān is proverbs, especially hidden proverbs that carry culture-specific meanings. The translator’s role in explicating the meanings of these culture-specific items is crucial. This research aims to identify and analyze Qur’ānic hidden proverbs using a technical reference (Esmaeeli, 1986) and to assess translation quality with Na Pham’s (2005) translation quality assessment model. In this study, two translation forms, AI and human (Qarai), were compared for their treatment of Qur’ānic hidden proverbs. Data collection and analysis followed a descriptive-qualitative design. Twenty-one verses containing hidden proverbs and their translations by GPT 3.5 and Qarai were analyzed. The study results indicated that, in terms of translation quality, GPT 3.5 performed better than Qarai.

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Main Subjects

©2023 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.

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International Journal of Textual and Translation Analysis in Islamic Studies
Volume 1, Issue 4 - Serial Number 4
October 2023
Pages 351-367

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History

  • Receive Date: 25 June 2023
  • Revise Date: 13 August 2023
  • Accept Date: 12 September 2023
  • Publish Date: 01 October 2023

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