Isolated Iqlab checking rules based on speech recognition system

The act of learning and teaching of the Qur'an is the most important science for Muslim. The teacher and learner in this area they should have the provisions of tajweed rules when reading the Qur'an. There are numerous efforts made by previous systems on the development of feasible guiding techniques to the act of Tajweed. However, liking the major control variables of the practices of Tajweed in those approaches were neglected. As a way to fill this gap. This research will present a speech recognition system to recognize and identify the rules of Iqlab (???). The proposed system will be capable of recognizing, identify and point out the mismatch of the iqlab rules for the verses contains the rules which made by the expert teachers stored in a database. In addition, in this research will use Mel-Frequency Cepstral Coefficient (MFCC) and Hidden Markov Models (HMM) as feature extraction and feature classification respectively.

[1]  Igor S. Pandzic,et al.  Automatic lip synchronization by speech signal analysis , 2008, INTERSPEECH.

[2]  Akram M. Zeki,et al.  Holy Qur'an speech recognition system distinguishing the type of recitation , 2016, 2016 7th International Conference on Computer Science and Information Technology (CSIT).

[3]  Khurram Waheed,et al.  A robust algorithm for detecting speech segments using an entropic contrast , 2002, The 2002 45th Midwest Symposium on Circuits and Systems, 2002. MWSCAS-2002..

[4]  Mohd Yamani Idna Idris,et al.  Quranic Verse Recitation Recognition Module for Support in j-QAF Learning: A Review , 2008 .

[5]  Akram M. Zeki,et al.  Automatic Speech Recognition for the Holy Qur'an, A Review , 2016, ICDM 2016.

[6]  A. Zabidi,et al.  Pattern classification in recognizing Qalqalah Kubra pronuncation using multilayer perceptrons , 2012, 2012 International Symposium on Computer Applications and Industrial Electronics (ISCAIE).

[7]  Alfred Mertins,et al.  Automatic speech recognition and speech variability: A review , 2007, Speech Commun..

[8]  Mohammed A. Aabed,et al.  Arabic Diacritics based Steganography , 2007, 2007 IEEE International Conference on Signal Processing and Communications.

[9]  Ramzi A. Haraty,et al.  CASRA+: A Colloquial Arabic Speech Recognition Application , 2007 .

[10]  Noorzaily Mohamed Noor,et al.  MFCC-VQ APPROACHFOR QALQALAH TAJWEED RULE CHECKING , 2014 .