Abstract :
Abstract— The act of learning and teaching of the Holy Quran has become a scientific practice to Muslims around. The stakeholders are face with a huge challenge when it comes to the principle of application of Tajweed (that is, the rules guiding the pronunciation during recitation of the Quran). There are several efforts made by previous systems on the development of feasible guiding techniques to the act of Tajweed. Unfortunately, liking the major control variables of the practices of Tajweed in those approaches were neglected. In order to fill this gap, this research present a speech recognition system that distinguishes the types of Madd (elongate tone) or prolongation and the type of Qira’at (method of recitation) related to Madd. The proposed system is capable of recognising, identifying, pointing out the mismatch and discriminate between two types of Madd namely, The Soft Lengthening ???? ????? and The Exchange Prolongation ?? ????? rules for Hafss and Warsh for the verses contains the two rules, that were made by the expert found in a database. Furthermore, this study used Mel-Frequency Cepstral Coefficient (MFCC) and Hidden Markov Models (HMM) as feature extraction and feature classification respectively
Keyword :
Holy Quran; Tajweed; Qira’at; Sound, Mel-Frequency; Hidden Markov Models