Classification of Quranic letters based on their characteristics (Sifaat) for supporting Quranic teaching and learning /
Recitation of the Holy Quran with the correct Tajweed is essential for every Muslim. Islam encourages Quranic education since the early age of 4 – 6 years old, or the moment when a child can start talking fluently. The correct recitation of the Quran will indicate the correct meaning of the words of...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
Kuala Lumpur :
Kulliyyah of Engineering, International Islamic University Malaysia,
2019
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| Subjects: | |
| Online Access: | Click here to view 1st 24 pages of the thesis. Members can view fulltext at the specified PCs in the library. |
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| Summary: | Recitation of the Holy Quran with the correct Tajweed is essential for every Muslim. Islam encourages Quranic education since the early age of 4 – 6 years old, or the moment when a child can start talking fluently. The correct recitation of the Quran will indicate the correct meaning of the words of Allah. It is important to recite the Quranic verses according to its characteristics (sifaat) and point of articulations (makhraj). However, to this date, there are limited researches on classifying the Quranic letters according to the characteristics. In this study, the focus is given to the classification of the characteristics of the Quranic letters for the purpose of developing an automated self-learning system for supporting the conventional method of Quranic teaching and learning. The characteristics of Quranic letters without opposites are whistling, vibration, ease, leaning, repeating, diffusion, and elongation. The data was obtained by recording the pronunciation of the Quranic letters by 30 experts in Quranic recitation including 19 male and 11 female subjects. Several methods of feature extraction and analysis were implemented such as Formant Analysis, Power Spectral Density (PSD), and Mel Frequency Cepstral Coefficient (MFCC) to come out with the suitable features that can represent the correct characteristics of the Quranic letters. Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) were used as the classifiers with cross-validation as the resampling method to obtain the decision boundary of classification between the Quranic letters with specific characteristics and the other letters. The result has shown the classifier QDA with all features combined give the best result in classifying the Quranic letters into their characteristics (sifaat). The model for classifying the Quranic letters that has been obtained can be used in developing the automated system for Quranic teaching and learning. |
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| Physical Description: | xv, 90 leaves : colour illustrations ; 30cm. |
| Bibliography: | Includes bibliographical references (leaves 65-68). |