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Arabic Dialects Morphological Analyzers: A Survey

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Recent Innovations in Artificial Intelligence and Smart Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1061))

Abstract

Morphological analysis is a crucial component in natural language processing. For the Arabic language, many attempts have been conducted in order to build morphological analyzers. Despite the increasing attention paid to Arabic dialects, the number of morphological analyzers that have been built is not important compared to Modern Standard Arabic. In addition, these tools often cover a few dialects of Arabic such as Egyptian, Levantine, and Gulf, and don’t support currently all of them. In this paper, we present a literature review of morphological analyzers supporting Arabic dialects. We classify their building approaches and propose some guidelines to adapt them to a specific Arabic dialect.

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Notes

  1. 1.

    http://www.vistawide.com/arabic/arabic.htm.

  2. 2.

    http://www.goud.ma.

  3. 3.

    http://www.lsvbdarija.com.

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Author information

Authors and Affiliations

  1. Chouaib Doukkali University, El Jadida, Morocco

    Ridouane Tachicart

  2. Mohammadia School of Engineers, Mohammed V University, Rabat, Morocco

    Karim Bouzoubaa

  3. Université Lorraine, Villers-lès-Nancy, Nancy, France

    Salima Harrat & Kamel Smaïli

Authors
  1. Ridouane Tachicart
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  2. Karim Bouzoubaa
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  3. Salima Harrat
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  4. Kamel Smaïli
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Corresponding author

Correspondence to Ridouane Tachicart .

Editor information

Editors and Affiliations

  1. Faculty of Engineering & IT, The British University in Dubai, Dubai, United Arab Emirates

    Mostafa Al-Emran

  2. Faculty of Engineering & IT, The British University in Dubai, Dubai, United Arab Emirates

    Khaled Shaalan

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Tachicart, R., Bouzoubaa, K., Harrat, S., Smaïli, K. (2022). Arabic Dialects Morphological Analyzers: A Survey. In: Al-Emran, M., Shaalan, K. (eds) Recent Innovations in Artificial Intelligence and Smart Applications. Studies in Computational Intelligence, vol 1061. Springer, Cham. https://doi.org/10.1007/978-3-031-14748-7_11

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