Development of Quran Reciter Identification System Using MFCC and Neural Network

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.

[1]  Ratnadeep R. Deshmukh,et al.  A Comparative Study between MFCC and DWT Feature Extraction Technique , 2014 .

[2]  Shreya Narang,et al.  Speech Feature Extraction Techniques: A Review , 2015 .

[3]  Tun Hussein Onn.  Speaker identification system using MFCC procedure and noise reduction method , 2012 .

[4]  Amit Kumar Sahoo,et al.  STUDY OF SPEAKER RECOGNITION SYSTEMS , 2011 .

[5]  Christian Hacker,et al.  Revising Perceptual Linear Prediction (PLP) , 2005, INTERSPEECH.

[6]  Namrata Dave,et al.  Feature Extraction Methods LPC, PLP and MFCC In Speech Recognition , 2013 .

[7]  Mohd Shahrizal Bin Sunar,et al.  Verification of Quranic Verses in Audio Files using Speech Recognition Techniques , 2014 .

[8]  Thomas Fang Zheng,et al.  Speech unit category based short utterance speaker recognition , 2012, Comput. Sci. Inf. Syst..

[9]  Mohd Yamani Idna Idris,et al.  Quranic Verse Recitation Recognition Module for Support in j-QAF Learning: A Review , 2008 .

[10]  A. M. Ahmad,et al.  Mel Frequency Cepstral Coefficients for Speaker Recognition Using Gaussian Mixture Model-Artificial Neural Network Model , 2008 .

[11]  Babasaheb Ambedkar,et al.  A Comparative Study of Feature Extraction Techniques for Speech Recognition System , 2014 .

[12]  Mohd Shahrizal Sunar,et al.  Quranic verses verification using speech recognition techniques , 2015 .

[13]  Biing-Hwang Juang,et al.  A vector quantization approach to speaker recognition , 1985, ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[14]  Saifur Rahman,et al.  SPEAKER IDENTIFICATION USING MEL FREQUENCY CEPSTRAL COEFFICIENTS , 2004 .

[15]  Hamdy K. Elminir,et al.  Evaluation of Different Feature Extraction Techniques for Continuous Speech Recognition , 2012 .