Artificial Intelligence in Arabic-English Translation: Comparative Linguistic and Stylistic Analysis for Selected Qur’anic Verses

Authors

  • Asst. Prof. Ayad Enad Khalaf (PhD) Sunni Endowment Author
  • Iman A. Abdulrahman (MA) Madenat Alelem University College Author

DOI:

https://doi.org/10.69513/jnfh.v1.i.2.en4

Keywords:

Artificial intelligence, Arabic natural language processing Machine learning · Qur’anic NLP · Religious texts · Classical Arabic.

Abstract

Artificial intelligence (AI), in recent years, has become a very real tool that can aid society in addressing many issues, including the challenges faced in the translation. In recent years, Arabic-English or English-Arabic translations have been generally influenced by the technologically driven approaches, like Google translation machine, in handling meaning between the two languages during the translation. The ubiquity of computing has become apparent and has demonstrated that the Arabic-English or English-Arabic translations can be achieved using AI-driven tools. Data collection of the current study included translating some texts in the Holy Quran from Arabic into English to show how translation by AI differs from human translation in many aspects. By analysing these data, this study discusses adopting AI in Arabic-English Translation based on the subfields of AI; machine learning and natural language processing (NLP). The findings reveal that AI subfields can be developed further in Arabic-English Translation, especially machine learning and Natural Language Processing (NLP). ©THISISANOPENACCESSARTICLEUNDERTHECCBY LICENSE.http://creativecommons.org/licenses/by/4.0/ AI projects on Arabic-English translations need adequate funding to establish sound connection between AI and Arabic translations into other languages or vice versa. Absence of the funding would limit AI’s potential and its applicability to all forms of Arabic-English i.e., literary and techno-scientific text. The research concludes by providing examples of how these subfields are being developed in Arabic-English translations for future research.

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Author Biographies

References

- Al-Azami MM (2020) The history of the Qur’anic text from revelation to compilation: a comparative study with the old and new testaments, 2nd edn. Turath Publishing, London.

- Alqudsi, A., N. Omar, and K. Shaker, Arabic machine translation: a survey. Artificial Intelligence Review, 2014. 42(4): p. 549-572.

- Ameur, M.S.H., F. Meziane, and A. Guessoum, Arabic machine translation: A survey of the latest trends and challenges. Computer Science Review, 2020. 38: p. 100305.

- Atwell E, Habash N, Louw B, Abu Shawar B, McEnery T, Zaghouani W, El-Haj M (2010) Understanding the Quran: a new grand challenge for computer science and artificial intelligence. ACM-BCS Visions of Computer Science.

- Azmi AM, Alsaiari A (2014) A calligraphic based scheme to justify Arabic text improving readability and comprehension. Comput Hum Behav 39:177–186.

- Broussard, Meredith; Diakopoulos, Nicholas; Guzman, Andrea L.; Abebe, Rediet; Dupagne, Michel; Chuan, Ching Hua. Artificial Intelligence and Journalism. Journalism and Mass Communication Quarterly; 2019; 96, pp. 673-95. [DOI: https://dx.doi.org/10.1177/1077699019859901].

- Castro, Daniel; New, Joshua. The Promise of Artificial Intelligence. Washington, DC and Brussels; 2016; Available online: https://www2.datainnovation.org/2016-promise-of-ai.pdf (accessed on 1 November 2021).

- Deloitte. 2014. Demystifying Artificial Intelligence. New York: Deloitte.

- Elsherif, H.M. and T.R. Soomro, Perspectives of arabic machine translation. Journal of Engineering Science and technology, 2017. 12(9): p. 2315-2332.

- Farghaly A, Shaalan K (2009) Arabic natural language processing: challenges and solutions. ACM Trans Asian Lang Inf Process (TALIP) 8(4):14 Future Today Institute 2018.

- Habash NY (2010) Introduction to Arabic natural language processing. Synth Lect Hum Lang Technol 3(1):1–187.

- Hassaballah, Mahmoud; Awad, Ali Ismail. Deep Learning in Computer Vision; 1st ed. Hassaballah, Mahmoud; Awad, Ali Ismail. CRC Press/Taylor and Francis: Boca Raton, 2020; [DOI: https://dx.doi.org/10.1201/9781351003827].

- Huang F (2015). Improved Arabic dialect classification with social media data. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing: 2118-2126.

- Khalaf, Ayad Enad. (2017). “Metaphorical Meaning and its Effect on Interaction”. YOBE Journal of Language literature and Culture. Damaturu. Yobe State, Nigeria.Vol. (5). pp. 33-47.

- Khalaf, Ayad Enad & Othman M. Mahmood (2019)."The Role of Stylistic devices in the Formation of Equivalent Meaning in the Inter-lingual Transfer from Arabic to English". Midad Al-Adab Refereed Journal, Iraqi University, Baghdad, Iraq. Vol. (3). No.(Conferences of 2018-2019) pp.1121-1138.

- Khalaf, Ayad Enad (2020). "Metaphor for Teaching Philosophy". Journal of Linguistics and Translation Studies. Bayt Al-Hikma. Baghdad, Iraq. (No. (33) December 2020. pp. 9-24.

- Locker, Mic; Loucks, Jeff; Hupfer, Susanne; Jarvis, David. Seasoned Explorers: How Experienced TMT Organizations Are Navigating AI; Deloitte: New York, 2019.

- Mahmood, Othman Muhammed and Khalaf, Ayad Enad (2022). ‘A Pragmalinguistic Analysis of Selected Arabic to English Translations for the (polysemic) Word “زعم” “Za'am' in the Gracious Quran’. Journal of Surra Man Raa,University of Samarra, Salah Ad Din, Iraq. Vol.18. No: 74. 17th Year. December/2022) (pp.1421-1436).

- McCarthy, John. What Is Artificial Intelligence?. CogPrints; Stanford, 1998; Available online: http://cogprints.org/412/2/whatisai.ps (accessed on 30 September 2021).

- Meftouh K, Harrat S, Jamoussi S, Abbas M and Smaili K (2015). Machine translation experiments on PADIC: A parallel Arabic dialect corpus. In The 29th Pacific Asia Conference on Language, Information and Computation: 26–34.

- Pickthal, Muhammed Marmaduke. (1930). The Meaning of the Glorious Kuran. Glopal Gray (2018).

- Russell, Stuart, and Norvig eds. 2021. Artificial Intelligence: A Modern Approach, 4th ed. Harlow, UK: Pearson, Available online: https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-4th-Edition/PGM1263338.html.

- Salloum SA, AlHamad AQ, Al-Emran M, Shaalan K (2018) A survey of Arabic text mining. In: Shaalan K, Hassanien AE, Tolba F (eds) Intelligent natural language processing: trends and applications. Springer, Cham, pp 417–431.

- Zbib R, Malchiodi E, Devlin J, Stallard D, Matsoukas S, Schwartz R and Callison-Burch C (2012). Machine translation of Arabic dialects. In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational linguistics: Human Language Technologies. Association for Computational Linguistics: 49-59.

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Published

2024-06-28

Issue

Vol. 2 No. 2 (2024): Al-Noor Journal for Humanitied

Section

Articles

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How to Cite

Artificial Intelligence in Arabic-English Translation: Comparative Linguistic and Stylistic Analysis for Selected Qur’anic Verses. (2024). Al-Noor Journal for Humanities, 2(2). https://doi.org/10.69513/jnfh.v1.i.2.en4

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