An efficient holy Quran recitation recognizer based on SVM learning model

Joint Authors

Nahar, Khalid M. O.
al-Khatib, Raid M.
al-Shunnaq, Muawiyah A.
Barhush, Malik M.

Source

Jordanian Journal of Computetrs and Information Technology

Issue

Vol. 6, Issue 4 (31 Dec. 2020), pp.392-414, 23 p.

Publisher

Princess Sumaya University for Technology

Publication Date

2020-12-31

Country of Publication

Jordan

No. of Pages

23

Main Subjects

Islamic Studies

Abstract EN

Holy Quran recitation recognition refers to the process of identifying the type of recitation, among those authorized styles of recitation (“Qira’ah” in Arabic).

Several previous studies investigated the recitation rules (“Ahkam Al-Tajweed” in Arabic) that are applied by readers or reciters while reading the Holy Quran aloud, but no study has examined the problem of tracking the type of recitation used in the reading.

Through this research, we can assist Holy Quran students to easily learn the perfect and accurate recitation by successfully applying Ahkam Al-Tajweed and help them distinguish between different recitations or "Qira’ah".

In this paper, a recognition model is conducted to recognize the “Qira’ah” from the corresponding Holy Quran acoustic wave.

This model was built upon three phases; the first phase is the Mel-Frequency Cepstrum Coefficients (MFCC) feature extraction of the acoustic signal and labeling it, the second phase is training Support Vector Machine (SVM) learning model the labeled features and finally, recognizing “Qira’ah” based on this trained model.

To attain this, we have built our corpus, which has 10 categories, each of which is labeled as one type of Holy Quran recitation or “Qira’ah”.

Different machine learning algorithms were applied and compared.

Experimental results proved the superiority of our proposed SVM-based recognition model for “Qira’ah” over other machine learning algorithms with a success rate of 96%.

American Psychological Association (APA)

Nahar, Khalid M. O.& al-Khatib, Raid M.& al-Shunnaq, Muawiyah A.& Barhush, Malik M.. 2020. An efficient holy Quran recitation recognizer based on SVM learning model. Jordanian Journal of Computetrs and Information Technology،Vol. 6, no. 4, pp.392-414.
https://search.emarefa.net/detail/BIM-1415807

Modern Language Association (MLA)

Nahar, Khalid M. O.…[et al.]. An efficient holy Quran recitation recognizer based on SVM learning model. Jordanian Journal of Computetrs and Information Technology Vol. 6, no. 4 (Dec. 2020), pp.392-414.
https://search.emarefa.net/detail/BIM-1415807

American Medical Association (AMA)

Nahar, Khalid M. O.& al-Khatib, Raid M.& al-Shunnaq, Muawiyah A.& Barhush, Malik M.. An efficient holy Quran recitation recognizer based on SVM learning model. Jordanian Journal of Computetrs and Information Technology. 2020. Vol. 6, no. 4, pp.392-414.
https://search.emarefa.net/detail/BIM-1415807

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 411-414

Record ID

BIM-1415807