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Unlocking the language barrier: A Journey through Arabic machine translation

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Abstract

Arabic Machine Translation (MT) has gained considerable attention from the research community due to the widespread use of Arabic as one of the world’s major languages. While significant progress has been made in this field, the quality of Arabic MT systems still lags behind that of some other languages. This survey paper aims to provide a comprehensive overview of Arabic MT by addressing its challenges, highlighting previous research studies, and discussing the field’s current state. The survey begins by introducing the characteristics of the Arabic language and the specific challenges it poses for translation. It then summarises the key research studies and explores the available tools and resources for building and evaluating Arabic MT systems. Additionally, the survey examines the strengths and weaknesses of existing techniques used in Arabic-English (and English-Arabic) machine translation, focusing on neural machine translation (NMT) approaches. By comparing different NMT methods and addressing linguistic and technical challenges, this paper offers valuable insights for researchers and professionals in Arabic MT. The findings, critiques, and open issues presented in this survey can serve as a foundation for further research and improvement in Arabic MT, providing a valuable resource for those interested in advancing the field.

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  1. Laboratory of Intelligent Systems and Applications, University of Sidi Mohamed Ben Abdellah, Route d’Imouzzer, Fez, Fez-Meknes, 2202, Morocco

    Fatima Zahra El Idrysy, Soufiane Hourri, Ikram El Miqdadi, Assia Hayati, Yassine Namir, Bassma Ncir & Jamal Kharroubi

  2. Laboratory of Process, Industrial Signals and Computer Science, University of Cadi Ayyad, Route Dar Si Aissa, Safi, Marrakech-Safi, 46000, Morocco

    Soufiane Hourri

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El Idrysy, F.Z., Hourri, S., El Miqdadi, I. et al. Unlocking the language barrier: A Journey through Arabic machine translation. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-19551-8

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  • DOI: https://doi.org/10.1007/s11042-024-19551-8

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