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Lahjawi: Arabic Cross-Dialect Translator

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3A6WXVZH26" target="_blank" >RIV/00216208:11320/26:6WXVZH26 - isvavai.cz</a>

  • Alternative codes found

    RIV/00216208:11320/26:XZCG76TJ

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Lahjawi: Arabic Cross-Dialect Translator

  • Original language description

    In this paper, we explore the rich diversity of Arabic dialects by introducing a suite of pioneering models called Lahjawi. The primary model, Lahjawi-D2D, is the first designed for cross-dialect translation among 15 Arabic dialects. Furthermore, we introduce Lahjawi-D2MSA, a model designed to convert any Arabic dialect into Modern Standard Arabic (MSA). Both models are fine-tuned versions of Kuwain-1.5B1 an in-house built small language model, tailored for Arabic linguistic characteristics. We provide a detailed overview of Lahjawi’s architecture and training methods, along with a comprehensive evaluation of its performance. The results demonstrate Lahjawi’s success in preserving meaning and style, with BLEU scores of 9.62 for dialect-to-MSA and 9.88 for dialect-to-dialect tasks. Additionally, human evaluation reveals an accuracy score of 58% and a fluency score of 78%, underscoring Lahjawi’s robust handling of diverse dialectal nuances. This research sets a foundation for future advancements in Arabic NLP and cross-dialect communication technologies. © 2024 Association for Computational Linguistics.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2025

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Int. Conf. Comput. Linguist., COLING - WACL, Workshop Arab. Corpus Linguist. - Proc. Workshop

  • ISBN

    979-8-89176-220-6

  • ISSN

  • e-ISSN

  • Number of pages

    13

  • Pages from-to

    12-24

  • Publisher name

    Association for Computational Linguistics (ACL)

  • Place of publication

  • Event location

    Abu Dhabi

  • Event date

    Jan 1, 2026

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article