Accuracy of Artificial Intelligence (AI) in Arabic Translation of Malay Idiomatic Phrases

Muhammad Luqman Ibnul Hakim Mohd Saad, Razimi Zakaria, Mohd Sollah Mohamed, Mohd Baharim Mayidin and Tengku Mohd Farid Tengku Abdul Aziz
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Muhammad Luqman Ibnul Hakim Mohd Saad: Academy of Language Studies, Universiti Teknologi MARA (UiTM) Kelantan Branch, Malaysia
Razimi Zakaria: Academy of Language Studies, Universiti Teknologi MARA (UiTM) Kelantan Branch, Malaysia
Mohd Sollah Mohamed: Academy of Language Studies, Universiti Teknologi MARA (UiTM) Kelantan Branch, Malaysia
Mohd Baharim Mayidin: Academy of Language Studies, Universiti Teknologi MARA (UiTM) Kelantan Branch, Malaysia
Tengku Mohd Farid Tengku Abdul Aziz: Academy of Language Studies, Universiti Teknologi MARA (UiTM) Kelantan Branch, Malaysia

International Journal of Research and Innovation in Social Science, 2025, vol. 9, issue 7, 4435-4444

Abstract: This article evaluates the precision of Artificial Intelligence (AI), specifically Neural Machine Translation (NMT) techniques, in rendering Malay idiomatic expressions into Arabic. Idioms, being culture-specific linguistic entities, pose significant challenges due to their non-compositional meanings and deep cultural embeddedness. This article adopts a qualitative approach by synthesizing and analysing existing scholarly works on idiom translation and the distinctive linguistic features of the Malay-Arabic language pair. The findings indicate that, although NMT systems can perform literal translations with precision, their efficacy is substantially diminished when handling figurative language with cultural resonance. This may lead to semantic inaccuracies, cultural misinterpretations, or syntactically flawed outputs, directly affecting translation precision. The article highlights the gap between literal and figurative translation capabilities in modern AI. It emphasizes the need for enhanced cultural and contextual understanding in NMT models to improve their accuracy, especially for low-resource language pairs such as Malay and Arabic.

Date: 2025
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