Development of Automated Tajweed Checking System for Children in Learning Quran

Abstract

Quran is learned at the early stage of Muslim children and usually taught by the religious teachers. It must be recited with precise and correct tajweed in order to avoid the misunderstanding of its meaning. Sometimes the children recite Quran without the presence of the teacher which the children tend to recite Quran wrongly since there is no guidance. Besides, different children have different learning style since some are visual learners and others are audio learners. In order to help the children to learn Quran in an attractive way, an Automated Tajweed Checking System for Children in Learning Quran is proposed. This system not intended to replace the role of the teachers but to attract the children in learning Quran and help the children to learn Quran without the presence of the teachers. The method of the project uses the concept of voice recognition. In voice recognition there are a few steps involve which are pre-processing, feature extraction, feature classification and recognition. The feature extraction technique used is Mel-Frequency Cepstral Coefficient (MFCC) while for feature classification and recognition technique used is Hidden Markov Model (HMM). This proposed system is believed to recognize recitation efficiently, thus helping children in learning Quran once completed.