Educational System for the Holy Quran and Its Sciences for Blind and Handicapped People Based on Google Speech API

ISSN Print: 1945-3116
ISSN Online: 1945-3124
www.scirp.net/journal/jsea
E-mail: [email protected]

Citations

"Educational System for the Holy Quran and Its Sciences for Blind and Handicapped People Based on Google Speech API"
written by Samir A. Elsagheer Mohamed, Allam Shehata Hassanin, Mohamed Tahar Ben Othman,
published by Journal of Software Engineering and Applications, Vol.7 No.3, 2014

has been cited by the following article(s):

[1]	Rancang Bangun Aplikasi Hafalan Al-Quran dengan Google Speech API Berbasis Android
	Jurnal Rekayasa …, 2022

[2]	Implementation of the Peer Tutor Model as an Effort to Increase the Effectiveness of Reading and Writing the Qur'an
	ENDLESS: International Journal of Future Studies, 2022

[3]	K. KARPAGASARAVANAKUMARc
	2021

[4]	Towards a speech therapy support system based on phonological processes early detection
	2020

[5]	Speech Command Recognition in Computationally Constrained Environments with a Quadratic Self-organized Operational Layer
	2020

[6]	Quranic Reciter Recognition: A Machine Learning Approach
	Advances in Science, Technology and Engineering Systems Journal, 2019

[7]	Deep Learning Approaches for Understanding Simple Speech Commands
	2018

[8]	A Case-Based System Architecture based on Situation-Awareness for Speech Therapy.
	2018

[9]	E-Iqra': Mobile Application for Learning Al-Quran Using Voice Recognition
	2018

[10]	An automatic question answering system for the Arabic Quran
	2017

[11]	Displayed Features of a Student with High-Functioning Autism During Qur'anic Learning
	Islamic Perspectives on Science and Technology, 2016

[12]	Automatic speech recognition
	2015

[13]	Automatic speech recognition An evaluation of Google Speech
	Thesis, 2015

[14]	Exploring Qur'an by using Aspects and Dependencies
	2015

[15]	DISPLAYED FEATURES OF A STUDENT WITH HIGH FUNCTIONING AUTISM DURING QURANIC LEARNING: A CASE STUDY
	2014

[16]	SMART GLASSES FOR THE VISUALLY IMPAIRED PEOPLE

[1]	Towards a speech therapy support system based on phonological processes early detection Computer Speech & Language, 2021 DOI:10.1016/j.csl.2020.101130

[2]	Deep Learning Approaches for Understanding Simple Speech Commands 2020 IEEE 40th International Conference on Electronics and Nanotechnology (ELNANO), 2020 DOI:10.1109/ELNANO50318.2020.9088863

[3]	Quranic Reciter Recognition: A Machine Learning Approach Advances in Science, Technology and Engineering Systems Journal , 2019 DOI:10.25046/aj040621

[4]	Islamic Perspectives on Science and Technology 2016 DOI:10.1007/978-981-287-778-9_24