JSEA  Vol.7 No.4 , April 2014
Virtual Learning System (Miqra’ah) for Quran Recitations for Sighted and Blind Students

Quran has ten famous recitations and twenty different narrations. It is well known that the best way is to learn from qualified and authentic scientists (Sheikh's) in one or more of these narrations. Due to 1) the widespread of the Internet and the ease of use and availability of computers and the smart phones that enables access to the Internet; 2) the business of people hindering them to attend physical learning environments; and 3) the very few number of elder licensed scientists, we have developed a virtual learning system (Electronic Miqra’ah). Scientists can supervise remotely the registered students. Students (from different ages) can register from anywhere in the world given that they have Internet connection. Students can interact with the scientist in real time so that they can help them memorize (Tahfeez), guide them for error correction, and give them lectures or lessons through virtual learning rooms. The targeted groups of users can be nonblind people, blind people, manual-disabled people and illiterate people. We have developed this system such that it takes the commands via voice in addition to the normal inputs like mouse and keyboard. Users can dictate the commands to the system orally and the system recognizes the spoken phrases and executes them. We have developed an efficient speech recognition engine that is speaker independent and accent independent. The system administrators create several virtual learning rooms and register the licensed scientists. Administrators prepare a daily schedule for each room. Students can register to any of these rooms by pronouncing its name. Each student is allocated a portion of time where he/she can interact directly by voice with the scientist. Other students can listen to the current student’s recitation and the error corrections, guidance or lessons from the scientists.

Cite this paper
Mohamed, S. , Hassanin, A. and Othman, M. (2014) Virtual Learning System (Miqra’ah) for Quran Recitations for Sighted and Blind Students. Journal of Software Engineering and Applications, 7, 195-205. doi: 10.4236/jsea.2014.74021.
[1]   Islam City Website. http://www.islamicity.com/mosque/quran/

[2]   Islam Way Website. The Most Famous Broadcast Website about Islam. http://en.islamway.net/

[3]   Quran Readings, Wikipidia English Webpage. http://en.wikipedia.org/wiki/Qur%27an_recitation

[4]   Carnegie Mellon University (2010) Sphinx—Speech Recognition Toolkit.

[5]   Lamere, P., Kwok, P., Gouvea, E. B., Raj, B., Singh, R., Walker, W. and Wolf, P. (2003) The CMU SPHINX-4 Speech Recognition System. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 46, 37-51.

[6]   Abushariah, M.A.M., Ainon, R.N., et al. (2010) Natural Speaker-Independent Arabic Speech Recognition System Based on Hidden Markov Models Using Sphinx Tools. 2010 International Conference on Computer and Communication Engineering (ICCCE), Kuala Lumpur, 11-12 May 2010, 1-6.

[7]   Satori, H., Harti, M. and Chenfour, N. (2007) Introduction to Arabic speech recognition using Cmusphinx System. Information and Communication Technologies International Symposium, Fes, 3-5 July 2007, 4 Pages.

[8]   Hyassat, H. and Abu Zitar, R. (2008) Arabic Speech Recognition Using SPHINX Engine. International Journal of Speech Technology, 9, 133-150.

[9]   Cambridge (2010) HTK—Hidden Markov Model Toolkit—Speech Recognition Toolkit.

[10]   Young, S., Evermann, G., Gales, M., Hain, T., Kershaw, D., Liu, X., Moore, G., Odell, J., Ollason, D., Povey, D., Valtchev, V. and Woodland, P. (1996) The HTK Book. Cambridge University Press, Cambridge.

[11]   Shaikh, M., Memon, N. and Wiil, U.K. (2011) Extended Approximate String Matching Algorithms to Detect Name Aliases. 2011 IEEE International Conference on Intelligence and Security Informatics (ISI), Beijing, 10-12 July 2011, 216-219.

[12]   Navarro, G. (2001) A Guided Tour to Approximate String Matching. ACM Computing Surveys, 33, 31-88. http://dx.doi.org/10.1145/375360.375365

[13]   Gusfield, D. (1997) Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology. Cambridge University Press, Cambridge, 263-264.

[14]   Mumble: An Open Source, Low-Latency, High Quality Voice Chat Software.

[15]   Rothbucher, M., Habigt, T., Feldmaier, J. and Diepold, K. (2010) Integrating a HRTF-Based Sound Synthesis System into Mumble. 2010 IEEE International Workshop on Multimedia Signal Processing (MMSP), 4-6 October 2010, 24-28. http://dx.doi.org/10.1109/MMSP.2010.5661988

[16]   Valin, J.M., Vos, K. and Terriberry, T. (2012) Definition of the Opus Audio Codec. IETF RFC 6716.

[17]   Comparison between Mumble, Skype, and Ventrilo. https://mmo-mumble.com/help/comparisonchart

[18]   Henning, M. (2004) A New Approach to Object-Oriented Middleware. IEEE Internet Computing, 8, 66-75. http://dx.doi.org/10.1109/MIC.2004.1260706

[19]   Khan, S., Qureshi, K. and Rashid, H. (2010) Performance Comparison of ICE, HORB, CORBA and Dot NET Remoting Middleware Technologies. International Journal of Computer Applications, 3, 15-18.