Leveraging AI-Powered Neural Machine Translation to Bridge the Gap: Translating Arabic Islamic Terminology into English

dc.authorscopusid 59372608300
dc.authorscopusid 59373038500
dc.authorscopusid 59372894200
dc.contributor.author Alharazi, A.F.A.
dc.contributor.author Alhebshi, S.H.S.
dc.contributor.author Taleb, N.R.M.
dc.date.accessioned 2024-11-15T19:39:37Z
dc.date.available 2024-11-15T19:39:37Z
dc.date.issued 2024
dc.department Okan University en_US
dc.department-temp Alharazi A.F.A., Universiti Malaya, Federal Territory of Kuala Lumpur, Kuala Lumpur, 50603, Malaysia; Alhebshi S.H.S., Sana’a University, Yemen; Taleb N.R.M., Istanbul Okan University, Turkey en_US
dc.description.abstract This paper assesses the appropriateness of NMT in translating Arabic Islamic terms into English, determining the main issues, and providing solutions. Some of the key concerns highlighted in the study are the scarcity of large corpora, the inability of NMT to deal with specific features of languages and the lack of adequate context and cultural supplements. In response to these challenges, four main recommendations have been highlighted in the report as follows. First, it prescribes the formation of special corpora containing various Islamic materials like the Quran, Hadiths, and theological writings. This will help to feed NMT systems with the inherent contextually relevant content data for the most work-related tasks. Secondly, it recommends the integration of other approaches with NMT such as rule-based and statistical translation that can handle idiomatic expressions and contextual interpretation. Third, it adopts the post-editing technique whereby the machine-translated text is checked by human translators to ensure adherence to cultural and contextual considerations. Lastly, the report urges more multi-ethnic cooperation among researchers, innovators, and translators to improve the accuracy and usefulness of translations. The paper finds that although NMT has advanced greatly in the field of translation technology, there are still challenges in translating complicated works in the Arabic and Islamic contexts. The adoption of these suggestions could enhance the quality of translations by a significant notch, thus producing translations that are more precise and sensitive to cultural differences. Thus, the conclusions drawn from the research affect the development of new technologies and cooperation in machine translation. © (2024), (Elite Scientific Publications). All rights reserved. en_US
dc.identifier.citationcount 0
dc.identifier.doi 10.57239/PJLSS-2024-22.2.00541
dc.identifier.endpage 7164 en_US
dc.identifier.issn 1727-4915
dc.identifier.issue 2 en_US
dc.identifier.scopus 2-s2.0-85206850413
dc.identifier.scopusquality Q4
dc.identifier.startpage 7150 en_US
dc.identifier.uri https://doi.org/10.57239/PJLSS-2024-22.2.00541
dc.identifier.uri https://hdl.handle.net/20.500.14517/7016
dc.identifier.volume 22 en_US
dc.language.iso en
dc.publisher Elite Scientific Publications en_US
dc.relation.ispartof Pakistan Journal of Life and Social Sciences en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 0
dc.subject AI-Powered en_US
dc.subject Arabic Islamic en_US
dc.subject Neural Machine en_US
dc.subject Terminology en_US
dc.subject Translation en_US
dc.title Leveraging AI-Powered Neural Machine Translation to Bridge the Gap: Translating Arabic Islamic Terminology into English en_US
dc.type Article en_US

Files