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This research is concerned with facilitating the use of Al Qaeda Al Norania as an important Learning method in pronunciation proficiency of Arabic Language and Holy Qur'an. Speech Verification techniques were applied to detect how close the trainee's pronunciation is to the guaranteed reference reader. The impact of the number of coefficients and parameterization of Mel-Frequency Cepstral Coefficients (MFCC) on verification accuracy was tested and compared. Al Qaeda Al Norania records and HTK toolbox were used to generate the best verification model for selected Arabic Syllable. General Terms Hidden Markov Models (HMM), Mel-Frequency Cepstral Coefficient (MFCC), Arabic Speech Verification, HTK Toolbox .

Comparative Evaluation of Different Mel-Frequency Cepstral Coefficient Features on Qura&apos;nic-Arabic Verification

Comparative Evaluation of Different Mel-Frequency Cepstral Coefficient Features on Qura'nic-Arabic Verification