Holy Qur'an Speech Recognition System Distinguishing The Type of prolongation

  • Bilal Yousfi Kulliyyah of Information and Communication Technology (KICT), International Islamic University Malaysia
  • Akram M. Zeki Kulliyyah of Information and Communication Technology (KICT), International Islamic University Malaysia
  • Aminah Haji Kulliyyah of Information and Communication Technology (KICT), International Islamic University Malaysia

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 المد اللين and The Exchange Prolongation مد البدل 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

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Published
2018-06-26
How to Cite
YOUSFI, Bilal; ZEKI, Akram M.; HAJI, Aminah. Holy Qur'an Speech Recognition System Distinguishing The Type of prolongation. Sukkur IBA Journal of Computing and Mathematical Sciences, [S.l.], v. 2, n. 1, p. 36-43, june 2018. ISSN 2522-3003. Available at: <http://journal.iba-suk.edu.pk:8089/SIBAJournals/index.php/sjcms/article/view/61>. Date accessed: 17 july 2018. doi: https://doi.org/10.30537/sjcms.v2i1.61.
Section
Research Articles