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Development of Quran reciter identification system using MFCC and neural network

Asda, Tayseer Mohammed Hasan and Gunawan, Teddy Surya and Kartiwi, Mira and Mansor, Hasmah (2016) Development of Quran reciter identification system using MFCC and neural network. TELKOMNIKA Indonesian Journal of Electrical Engineering, 17 (1). pp. 168-175. ISSN 2302-4046

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Abstract

Currently, the Quran is recited by so many reciters with different ways and voices. Some people like to listen to this reciter and others like to listen to other reciters. Sometimes we hear a very nice recitation of al-Quran and want to know who the reciter is. Therefore, this paper is about the development of Quran reciter recognition and identification system based on mel frequency cepstral coefficient (MFCC) feature extraction and artificial neural network (ANN). From every speech, characteristics from the utterances will be extracted through neural network model. In this paper a database of five Quran reciters is created and used in training and testing. The feature vector will be fed into neural network back propagation learning algorithm for training and identification processes of different speakers. Consequently, 91.2% of the successful match between targets and input occurred with certain number of hidden layers which shows how efficient are mel frequency cepstral coefficient (MFCC) feature extraction and artificial neural network (ANN) in identifying the reciter voice perfectly.

Item Type: Article (Journal)
Additional Information: 5588/51467
Uncontrolled Keywords: Speaker Identification, Mel Frequency Cepstral Coefficient (MFCC), Neural Network, Vector Quantization, Quran Reciter
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Dr Teddy Surya Gunawan
Date Deposited: 09 Aug 2016 09:54
Last Modified: 13 Apr 2017 12:08
URI: http://irep.iium.edu.my/id/eprint/51467

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