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A study on arabic phonemes towards an automatic teaching system for the recitation of Holy Qur{u2019}an / Fatma Shawky Abdelhamid Mohamed Khaled ; Supervised Ahmed M. Elbialy , Ahmed H. Kandil , Sahar A. Fawzi

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Fatma Shawky Abdelhamid Mohamed Khaled , 2017Description: 75 P. : charts , photographs ; 30cmOther title:
  • نظام تعرف اوتوماتيكى على الوحدات الصوتية [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering Summary: This thesis is part of ongoing integrated studies concerning classical Arabic recognition for both teaching and learning purposes. The major point of strength is using Alnorania rule for the first time as training and testing dataset to differentiate between Arabic phonemes based on their exits and characteristics. This presents a substantial contribution summing up recognition models for recognizing different features and tiny details of each letter. This work is a good seed for different speech synthesis or speech recognition projects later on
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.M.Sc.2017.Fa.S (Browse shelf(Opens below)) Not for loan 01010110074434000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.M.Sc.2017.Fa.S (Browse shelf(Opens below)) 74434.CD Not for loan 01020110074434000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering

This thesis is part of ongoing integrated studies concerning classical Arabic recognition for both teaching and learning purposes. The major point of strength is using Alnorania rule for the first time as training and testing dataset to differentiate between Arabic phonemes based on their exits and characteristics. This presents a substantial contribution summing up recognition models for recognizing different features and tiny details of each letter. This work is a good seed for different speech synthesis or speech recognition projects later on

Issued also as CD

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