Quran as holy book for Muslim consists of many rules which are needed to be considered in reading Quran verse properly. If the recitation does not meet all of those rules, the meaning of Quran verse recited will be different with its origins. Intensive learning is needed to be able to do correct recitation. However, the limitation of teachers and time to study Quran verse recitation together in a class could be an obstacle in Quran recitation learning. In order to minimize the obstacle and to ease the learning process we implement speech recognition techniques based on Mel Frequency Cepstral Coefficient (MFCC) features and Gaussian Mixture Model (GMM) modeling, we have successfully designed and developed Quran verse recitation learning software in prototype stage. This software is interactive multimedia software which has many features for learning flexibility and effectiveness. This paper explains the developing of speech recognition system for Quran learning software which is built with the ability to perform evaluation and correction in Quran recitation. In this paper, the authors present clearly the built and tested prototype of the system based on experiment data.
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