The purpose of this paper is to provide a structural overview of speech recognition system for developing Quranic verse recitation recognition with tajweed checking rules function. This function has been introduced, due to support the existing and manual method of talaqqi and musyafahah method in Quranic learning process, which described as face-to-face learning process between students and teachers. Here, the process of listening, correction and repetition of the correct Al-Quran recitation took place in real-time condition. However, this method is believed to become less effective and unattractive to be implemented, especially towards the young Muslim generation who are more attracted to the latest technology.
This paper focuses on the development of software prototype, mainly for developing an automated Tajweed checking rules engine, purposely for Quranic learning. It has been implemented and tested towards the j-QAF students at primary school in Malaysia.
The paper provides empirical insight about the viability and implementation of Mel-frequency cepstral coefficients (MFCC) algorithm of feature extraction technique and hidden Markov model (HMM) classification for recognition part, with the results of recognition rate reached to 91.95 percent (ayates) and 86.41 percent (phonemes), after been tested on sourate Al-Fatihah.
Based on the result, proved that the engine has a potential to be used as an educational tool, which helps the students read Al-Quran better, even without the presence of teachers (Mudarris)/parents to monitor them. Automated system with Tajweed checking rules capability functions could be another alternative due to support the existing method of manual skills of Quranic learning process, without denying the main role of teachers in teaching Al-Quran.
Special thanks are posed to University of Malaya for its funding in carrying out this research project. The authors are grateful to the project leader Professor Dato' Dr M.Y. Zulkifli Mohd Yusoff for valuable guidance and ideas, and to Emran Mohd. Tamil and Noorzaily Mohamed for helping in software development, as well as cultivating ideas in several aspects of this work. The authors gratefully acknowledge their support for this research.
Jamaliah Ibrahim, N., Yamani Idna Idris, M., Razak, Z. and Naemah Abdul Rahman, N. (2013), "Automated tajweed checking rules engine for Quranic learning", Multicultural Education & Technology Journal, Vol. 7 No. 4, pp. 275-287. https://doi.org/10.1108/METJ-03-2013-0012Download as .RIS
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