Features identification and classification of alphabet (ro) in leaning (Al-Inhiraf) and repetition (Al-Takrir) characteristics
—It is important for Muslim to recite the Quran properly with the correct Tajweed. which includes the use of correct characteristics (sifaat) and point of articulations (makhraj). To this date, there are limited researches done focusing on classifying the Quranic letters according to the charac...
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my.iium.irep.797292020-07-09T06:43:32Z http://irep.iium.edu.my/79729/ Features identification and classification of alphabet (ro) in leaning (Al-Inhiraf) and repetition (Al-Takrir) characteristics Khairuddin, Safiah Ahmad, Salmiah Embong, Abd Halim Nik Hashim, Nik Nur Wahidah Hassan, Surul Shahbudin BP134.S3 Quran and Science T Technology (General) —It is important for Muslim to recite the Quran properly with the correct Tajweed. which includes the use of correct characteristics (sifaat) and point of articulations (makhraj). To this date, there are limited researches done focusing 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, which are the focus in this paper are Leaning and Repeating, where both consists of ر) ro) alphabet. Several methods of feature extractions 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 best represent the correct characteristics of the alphabet. Once the features had been identified, Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) were used as the classifier. The results show that QDA with all 19 features trained achieved the highest percentage accuracy for both Leaning (اإلنحراف – Al-Inhiraf) and ّكرير) Repetition الت– Al-Takrir) characteristics with of 82.1% and 95.8% of accuracy respectively Institute of Electrical and Electronics Engineers Inc. 2019-03-28 Conference or Workshop Item NonPeerReviewed application/pdf en http://irep.iium.edu.my/79729/1/79729_Features%20Identification%20and%20Classification%20_conf.%20article.pdf application/pdf en http://irep.iium.edu.my/79729/2/79729_Features%20Identification%20and%20Classification%20_scopus.pdf Khairuddin, Safiah and Ahmad, Salmiah and Embong, Abd Halim and Nik Hashim, Nik Nur Wahidah and Hassan, Surul Shahbudin (2019) Features identification and classification of alphabet (ro) in leaning (Al-Inhiraf) and repetition (Al-Takrir) characteristics. In: "2019 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2019", 29 June 2019, Selangor. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8825067 10.1109/I2CACIS.2019.8825067 |
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BP134.S3 Quran and Science T Technology (General) Khairuddin, Safiah Ahmad, Salmiah Embong, Abd Halim Nik Hashim, Nik Nur Wahidah Hassan, Surul Shahbudin Features identification and classification of alphabet (ro) in leaning (Al-Inhiraf) and repetition (Al-Takrir) characteristics |
description |
—It is important for Muslim to recite the Quran
properly with the correct Tajweed. which includes the use of
correct characteristics (sifaat) and point of articulations
(makhraj). To this date, there are limited researches done
focusing 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, which are the
focus in this paper are Leaning and Repeating, where both
consists of ر) ro) alphabet. Several methods of feature
extractions 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 best represent the correct characteristics of the
alphabet. Once the features had been identified, Linear
Discriminant Analysis (LDA) and Quadratic Discriminant
Analysis (QDA) were used as the classifier. The results show that
QDA with all 19 features trained achieved the highest
percentage accuracy for both Leaning (اإلنحراف – Al-Inhiraf) and
ّكرير) Repetition
الت– Al-Takrir) characteristics with of 82.1% and
95.8% of accuracy respectively |
format |
Conference or Workshop Item |
author |
Khairuddin, Safiah Ahmad, Salmiah Embong, Abd Halim Nik Hashim, Nik Nur Wahidah Hassan, Surul Shahbudin |
author_facet |
Khairuddin, Safiah Ahmad, Salmiah Embong, Abd Halim Nik Hashim, Nik Nur Wahidah Hassan, Surul Shahbudin |
author_sort |
Khairuddin, Safiah |
title |
Features identification and classification of alphabet (ro) in leaning (Al-Inhiraf) and repetition (Al-Takrir) characteristics |
title_short |
Features identification and classification of alphabet (ro) in leaning (Al-Inhiraf) and repetition (Al-Takrir) characteristics |
title_full |
Features identification and classification of alphabet (ro) in leaning (Al-Inhiraf) and repetition (Al-Takrir) characteristics |
title_fullStr |
Features identification and classification of alphabet (ro) in leaning (Al-Inhiraf) and repetition (Al-Takrir) characteristics |
title_full_unstemmed |
Features identification and classification of alphabet (ro) in leaning (Al-Inhiraf) and repetition (Al-Takrir) characteristics |
title_sort |
features identification and classification of alphabet (ro) in leaning (al-inhiraf) and repetition (al-takrir) characteristics |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2019 |
url |
http://irep.iium.edu.my/79729/1/79729_Features%20Identification%20and%20Classification%20_conf.%20article.pdf http://irep.iium.edu.my/79729/2/79729_Features%20Identification%20and%20Classification%20_scopus.pdf http://irep.iium.edu.my/79729/ https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8825067 |
_version_ |
1672610177399914496 |