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| Élément Dublin Core | Valeur | Langue |
|---|---|---|
| dc.contributor.author | Hadjar Kherfane, Fatma | - |
| dc.date.accessioned | 2025-11-19T13:44:40Z | - |
| dc.date.available | 2025-11-19T13:44:40Z | - |
| dc.date.issued | 2025-05-28 | - |
| dc.identifier.uri | http://dspace.univ-tiaret.dz:80/handle/123456789/16853 | - |
| dc.description.abstract | The recitation of the Quran holds immense spiritual,cultural,and educational impor- tance within the Muslim world. Among the various modes of recitation,the Warsh style is notably prevalent in North Africa,particularly in Algeria,Morocco,and Tunisia. Accurate recitation requires mastery of the complex rules of Tajweed, which govern pro- nunciation,articulation,and rhythm.However,assessing the correctness of recitation remains largely dependent on human experts,posing challenges in terms of accessibility, scalability,and objectivity. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | University of Ibn Khaldoun Tiaret | en_US |
| dc.subject | Quranic recitation | en_US |
| dc.subject | Warsh style | en_US |
| dc.subject | Tajweed | en_US |
| dc.subject | deeplearning | en_US |
| dc.title | Speech Recognition and Deep Learning: A Focus on Quranic Recitation | en_US |
| dc.type | Thesis | en_US |
| Collection(s) : | Master | |
Fichier(s) constituant ce document :
| Fichier | Description | Taille | Format | |
|---|---|---|---|---|
| TH.M.INF.2025.03.pdf | 3,51 MB | Adobe PDF | Voir/Ouvrir |
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