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dc.contributor.authorHadjar Kherfane, Fatma-
dc.date.accessioned2025-11-19T13:44:40Z-
dc.date.available2025-11-19T13:44:40Z-
dc.date.issued2025-05-28-
dc.identifier.urihttp://dspace.univ-tiaret.dz:80/handle/123456789/16853-
dc.description.abstractThe 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.isoenen_US
dc.publisherUniversity of Ibn Khaldoun Tiareten_US
dc.subjectQuranic recitationen_US
dc.subjectWarsh styleen_US
dc.subjectTajweeden_US
dc.subjectdeeplearningen_US
dc.titleSpeech Recognition and Deep Learning: A Focus on Quranic Recitationen_US
dc.typeThesisen_US
Collection(s) :Master

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