ASR for Tajweed Rules: Integrated with Self-Learning Environments

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Ahmed AbdulQader Al-Bakeri 1,* Abdullah Ahmad Basuhail 1

1. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

* Corresponding author.


Received: 2 Jun. 2017 / Revised: 11 Jul. 2017 / Accepted: 1 Aug. 2017 / Published: 8 Nov. 2017

Index Terms

Automatic Speech Recognition (ASR), Acoustic model, Phonetic dictionary, Language model, Hidden Markov Model, Model View Controller (MVC)


Due to the recent progress in technology, the traditional learning setting in several fields has been renewed by different environments of learning, most of which involve the use of computers and networking to achieve a type of e-learning. With great interest surrounding the Holy Quran related research, only a few scientific research has been conducted on the rules of Tajweed (intonation) based on automatic speech recognition (ASR). In this research, the use of ASR and MVC design is proposed. This system enhances the learners’ basic knowledge of Tajweed and facilitates self-learning. The learning process that is based on ASR ensures that the students have the proper pronunciation of the verses of the Holy Quran. However, the traditional method requires that both students and teacher meet face-to-face. This requirement is a limitation to enhancing individuals’ learning. The purpose of this research is to use speech recognition techniques to correct students’ recitation automatically, bearing in mind the rules of Tajweed. In the final steps, the system is integrated with self-learning environments which depend on MVC architectures.

Cite This Paper

Ahmed AbdulQader Al-Bakeri, Abdullah Ahmad Basuhail, " ASR for Tajweed Rules: Integrated with Self-Learning Environments", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.9, No.6, pp.1-9, 2017. DOI:10.5815/ijieeb.2017.06.01


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