Development of quranic reciter identification system using MFCC and GMM classifier

Gunawan, Teddy Surya and Muhamat Saleh, Nur Atikah and Kartiwi, Mira (2018) Development of quranic reciter identification system using MFCC and GMM classifier. International Journal of Electrical and Computer Engineering, 8 (1). pp. 372-378. ISSN 2088-8708

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Abstract

Nowadays, there are many beautiful recitation of Al-Quran available. Quranic recitation has its own characteristics, and the problem to identify the reciter is similar to the speaker recognition/identification problem. The objective of this paper is to develop Quran reciter identification system using Mel-frequency Cepstral Coefficient (MFCC) and Gaussian Mixture Model (GMM). In this paper, a database of five Quranic reciters is developed and used in training and testing phases. We carefully randomized the database from various surah in the Quran so that the proposed system will not prone to the recited verses but only to the reciter. Around 15 Quranic audio samples from 5 reciters were collected and randomized, in which 10 samples were used for training the GMM and 5 samples were used for testing. Results showed that our proposed system has 100% recognition rate for the five reciters tested. Even when tested with unknown samples, the proposed system is able to reject it.

Item Type:	Article (Journal)
Additional Information:	5588/64205
Uncontrolled Keywords:	GMM; MFCC; Quranic recitation; Speaker identification
Subjects:	T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TS Manufactures
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User:	Prof. Dr. Teddy Surya Gunawan
Date Deposited:	12 Jun 2018 10:07
Last Modified:	12 Jun 2018 10:07
URI:	http://irep.iium.edu.my/id/eprint/64205

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