Transformer-based model for moroccan Arabizi-to-Arabic transliteration using a semi-automatic annotated dataset

Language models have recently achieved state-of-the-art results in tasks such as translation, sentiment analysis, and text classification for high-resource languages. However, dedicated models for low-resource languages remain scarce, largely due to a lack of annotated data and linguistic resources....

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Detalles Bibliográficos

Autores principales:	Soufiane Hajbi, Omayma Amezian, Mouhssine Ziyad, Issame El Kaime, Redouan Korchiyne, Younes Chihab
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Elsevier 2025-12-01
Colección:	International Journal of Information Management Data Insights
Materias:	Arabizi Arabic dialect Low resource language Transformer Transliteration NLP
Acceso en línea:	http://www.sciencedirect.com/science/article/pii/S2667096825000333
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