Development of Quranic Reciter Identification System using MFCC and GMM Classifier

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.

[1]  Douglas A. Reynolds,et al.  Deep Neural Network Approaches to Speaker and Language Recognition , 2015, IEEE Signal Processing Letters.

[2]  Patrick Kenny,et al.  Front-End Factor Analysis for Speaker Verification , 2011, IEEE Transactions on Audio, Speech, and Language Processing.

[3]  V. Tiwari.  MFCC and its applications in speaker recognition , 2010 .

[4]  Izzat Alsmadi,et al.  Online integrity and authentication checking for Quran electronic versions , 2017 .

[5]  Figen Ertaş,et al.  FUNDAMENTALS OF SPEAKER RECOGNITION , 2011 .

[6]  Teddy Surya Gunawan,et al.  Development of Quran Reciter Identification System Using MFCC and Neural Network , 2016 .

[7]  Thomas Fang Zheng,et al.  Improving Short Utterance Speaker Recognition by Modeling Speech Unit Classes , 2016, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

[8]  A. B. Poritz,et al.  Linear predictive hidden Markov models and the speech signal , 1982, ICASSP.

[9]  Jr. J.P. Campbell,et al.  Speaker recognition: a tutorial , 1997, Proc. IEEE.

[10]  Teddy Surya Gunawan,et al.  On the Characteristics of Various Quranic Recitation for Lossless Audio Coding Application , 2016, 2016 International Conference on Computer and Communication Engineering (ICCCE).

[11]  Daniel Garcia-Romero,et al.  Linear versus mel frequency cepstral coefficients for speaker recognition , 2011, 2011 IEEE Workshop on Automatic Speech Recognition & Understanding.

[12]  Priyanka Bansal,et al.  Speaker recognition using MFCC, shifted MFCC with vector quantization and fuzzy , 2015, 2015 International Conference on Soft Computing Techniques and Implementations (ICSCTI).