CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Verification System for Quran Recitation Recordings

by Ayat Hafzalla Ahmed, Sherif Mahdi Abdo
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 163 - Number 4
Year of Publication: 2017
Authors: Ayat Hafzalla Ahmed, Sherif Mahdi Abdo
10.5120/ijca2017913493

Ayat Hafzalla Ahmed, Sherif Mahdi Abdo . Verification System for Quran Recitation Recordings. International Journal of Computer Applications. 163, 4 ( Apr 2017), 6-11. DOI=10.5120/ijca2017913493

@article{ 10.5120/ijca2017913493,
author = { Ayat Hafzalla Ahmed, Sherif Mahdi Abdo },
title = { Verification System for Quran Recitation Recordings },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 163 },
number = { 4 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 6-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume163/number4/27381-2017913493/ },
doi = { 10.5120/ijca2017913493 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:09:13.579577+05:30
%A Ayat Hafzalla Ahmed
%A Sherif Mahdi Abdo
%T Verification System for Quran Recitation Recordings
%J International Journal of Computer Applications
%@ 0975-8887
%V 163
%N 4
%P 6-11
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Quran is the holy book of Allah which was revealed to Prophet Mohammed. Quran is written and recited in Arabic language, the language in which it was revealed. Muslims believe that the Quran is neither corrupted nor altered this is mainly due to maintaining its original text. The Quran should be recited in Arabic language as it is with neither additions nor subtractions. When the Arabs started to mix with the non Arabs as Islam spread, mistakes in Quran recitation started to appear, so the scholars had to record the rules of tajweed and write them down in order to preserve the Qur'an recitation as revealed by Allah. In this regard, it is necessary to preserve the authenticity and integrity of the Quran from all sorts of corruption or deletion. This paper provides an overview of the techniques used in voice recognition in the Quran recitation focusing on the techniques used, the advantages, and drawbacks. And proposed model of verification system for Quran verses.

References
  1. Abdou, Sherif Mahdy, and Mohsen Rashwan. "A Computer Aided Pronunciation Learning system for teaching the holy quran Recitation rules." 2014 IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA). IEEE, 2014.
  2. Zameer Ahmed Adhoni1, Husam Al Hamad1, Abdul Ahad Siddiqi2, Mohammd Parvez1, Zaheer Ahmed Adhoni3 “Cloud-based Online Portal and Mobile Friendly Application for the Holy Qur’an". Life Science Journal (2013); 10(12s) .http://www.lifesciencesite.com.
  3. S. Hamid “Computer aided pronunciation learning system using statistical based automatic speech recognition”. PhD thesis, Cairo University, Cairo, Egypt, 2005.
  4. Ahsiah. I, Noor. N.M, Idris. M.Y.I.” Tajweed checking system to support recitation.” ICACSIS (2013). ISBN: 978-979-1421-19-5
  5. A. Muhammad, “E-Hafiz: Intelligent System to Help Muslims in Recitation and Memorization of Quran,” Life Science …, vol. 9, no. 1, pp. 534–541, 2012.
  6. Silke M. W, (2012). Automatic Error Detection in Pronunciation Training: Where we are and where we need to go. Proceedings of the International Symposium on Automatic Detection of Errors in Pronunciation Training June 6 - 8, 2012 KTH, Stockholm, Sweden.
  7. H. Franco et al., “The SRI EduSpeak system: Recognition and pronunciation scoring for language learning”, Proc. of InSTIL, Scotland, 123-128, 2000.
  8. Harrag, A. and Mohamadi T., " QSDAS: New Quranic Speech Database for Arabic Speaker Recognition", the Arabian Journal for Science and Engineering, vol. 35, no. 2C, pp. 7-13, December (2010).
  9. Ammar Mohammed 1*, Mohd Shahrizal Bin Sunar 2,.” Quranic Verses Verification using Speech Recognition Techniques” Jurnal Teknologi (Sciences & Engineering) 73:2 (2015), 99–106.
  10. N. J. I. M. Y. I. I. E. M. T. M. Y. Zaidi Razak " ،†Quranic Verse Recitation Recognition Module for Support in j-QAF Learning: A Review "،IJCSNS International Journal of Computer Science and Network Security, VOL.8 No.8, August (2008).2118.
  11. M. Ursin (2002). “Triphone Clustering in Finnish Continuous Speech Recognition.” Master Thesis, Department of Computer Science, Helsinki University of Technology, Finland.
  12. Nengheng Zheng, Tan Lee and P. C. Ching, “Integration of Complementary Acoustic Features for Speaker Recognition”, International Journal of Signal Processing Letter, IEEE, vol. ASSP-14, no.3, pp. 181-184, (2007).
  13. ]A. M. Ahmad, S. Ismail, D.F. Samaon, 2004.” Recurrent Neural Network with Backpropagation through Time for Speech Recognition.” IEEE International Symposium on Communications & Information Technology, 2004. ISCIT '04. Volume 1,pp.98-102.
  14. H. Tabbal, W. El-Falou and B. Monla, Analysis and Implementation of a “Quranic verses delimitation system in audio files using speech recognition techniques. Proc. of the IEEE Conf. of 2nd Information and Communication Technologies 2006; 2(1): 2979 – 2984.
  15. A. Hagen and B. Pellom, “Data driven sub-word unit modeling for speech recognition and its application to interactive reading tutors,” in Proc. European Conference on Speech Communication and Technology, Lisbon, Portugal, Sept. 2005, pp. 2757–2760.
  16. J. Mostow, et al., “Evaluation of an automated Reading Tutor that listens: Comparison to human tutoring and classroom instruction”. Journal of Educational Computing Research, 29(1), 61-117, 2003.
  17. D. A. Williams, “Knowing what you don't know: roles for confidence measures in automatic speech recognition”, Ph.D. thesis, Department of Computer Sciences, University of Sheffield, Sheffield, United Kingdom, 1999.
  18. Nurul Wahidah Arshad, Suriazalmi Mohd Sukri, Lailatul Niza Muhammad, Hasan Ahmad, Rosyati Hamid, Faradila Naim, Noor Zirwatul Ahlam Naharuddin “Makhraj Recognition for Al-Quran Recitation using MFCC“. International Journal of Intelligent Information Processing (IJIIP).Volume4, Number2, June 2013.
  19. Bushra Abro, Asma Batool Naqvi and Ayyaz Hussain, “Qur’an Recognition For The Purpose Of Memorisation Using Speech Recognition Technique”, 978-1-4673-2252-2/12/$31.00 © (2012) IEEE.
  20. M. Al-Zabibi, “An Acoustic–Phonetic Approach in Automatic Arabic Speech Recognition,” The British Library in Association with UMI, 1990.
  21. J. Deller, J. Proakis, J.H. Hansen, “Discrete- Time Processing of Speech Signal,” Macmillan, NY, 1993.
  22. Bassam A. Q. Al-Qatab , Raja N. Ainon, “Arabic Speech Recognition Using Hidden Markov Model Toolkit(HTK)”, 978-1-4244-6716-711 0/$26.00 ©(2010) IEEE.
  23. J. H. M. Daniel Jurafsky. Speech and Language Processing, An introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Prentice Hall, Upper Saddle River, New Jersey 07458,(2000).
  24. S. Hamed, M. Rashwan, “Automatic Generation of Hypotheses for Automatic Diagnosis of Pronunciation Errors” First International Conference on Arabic Language Resources and Tools, Cairo, Egypt, 22-23 April 2004.
  25. Abdou Sherif Mahdy and Mohsen Rashwan “Performance Evaluations for a Computer Aided Pronunciation Learning System”.
  26. Noor Jamaliah Ibrahim, Zaidi Razak, Mohd Yakub, Zulkifli Mohd Yusoff, Mohd Yamani Idna Idris and Emran Mohd Tamil, Quranic verse Recitation feature extraction using Mel-Frequenc Cepstral Coefficients (MFCC). Proc. the 4th IEEE Int. Colloquium on Signal Processing and its Application (CSPA) 2008, Kuala Lumpur, MALAYSIA. (2008).
  27. SUVing, Automatic Silence/Unvoiced/Voiced Classification of Speech. Undergraduate Coursework, Department of Computer Science, the University of Sheffield, UK. (1999).
  28. H.Hermansky, 1990.” Perceptual linear predictive (PLP) analysis of speech”. The Journal of the Acoustical Society of America -April 1990. Volume 87, Issue 4, pp. 1738-1752.
  29. V.K. Medisetti and D.B. William, 1999.” Digital Signal Processing Handbook.” CRC Press LLC.
  30. S.V. Vuuren, 1996.”Comparison of Text-Independent Speaker Recognition Methods on Telephone Speech with Acoustic Mismatch”. Proceeding (ICSLP)96, Vol:3, Philadelphia, PA. pp. 1788-1791.
  31. Azmi, A. M., and Almajed, R. S. 2013. A Survey of Automatic Arabic Diacritization Techniques. Natural Language Engineering. 1–19.
Index Terms

Computer Science
Information Sciences

Keywords

Quran Arabic Language Quran recitation Computer Aided Pronunciation Learning.

Powered by PhDFocusTM