IDEAS home Printed from https://ideas.repec.org/h/spr/lnichp/978-3-032-06725-8_2.html

A Multi-Level Arabic Text Diacritization System

In: Technological Innovations for Sustainable Development

Author

Listed:
  • Ali Mijlad

    (ENSATe, Abdelmalek Essaadi University, SIGL Laboratory)

  • Yacine El Younoussi

    (ENSATe, Abdelmalek Essaadi University, SIGL Laboratory)

Abstract

This paper presents a multi-level Arabic diacritization system designed to restore diacritics for undiacritized Arabic text. This kind of systems is crucial for Arabic-related NLP tasks and aids learners and individuals with learning difficulties, such as dyslexia or visual impairments. Our system uses a two-level approach: a word-based level and a letter-based level, both employing an encoder-decoder model with a local predictive Luong attention mechanism. The combined model demonstrates good performance with a 22.47% diacritic error rate, significantly surpassing single-level models while maintaining competitive performance despite using a smaller dataset compared to previous studies.

Suggested Citation

  • Ali Mijlad & Yacine El Younoussi, 2025. "A Multi-Level Arabic Text Diacritization System," Lecture Notes in Information Systems and Organization, in: Badr-Eddine Boudriki Semlali & Ikram Ben Abdel Ouahab & Fabio Angeletti (ed.), Technological Innovations for Sustainable Development, pages 17-27, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-06725-8_2
    DOI: 10.1007/978-3-032-06725-8_2
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:lnichp:978-3-032-06725-8_2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.