Papers by Mahmoud Reda

1 papers
Arabic Diacritization Using Morphologically Informed Character-Level Model (2024.lrec-main)

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Challenge: Diacritics are typically omitted in Arabic writings and the reader needs to guess the proper diacritics as they are reading.
Approach: They propose a morphologically informed character-level model that can recover both types of diacritics simultaneously.
Outcome: The proposed model achieves lowest word-level diacritization error rate for Classical Arabic, MSA, and two dialectal Arabic texts.

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