基于深度学习的智能框架,用于大流行病期间的在线古兰经学习

IF 2.4 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Applied Computational Intelligence and Soft Computing Pub Date : 2023-12-22 DOI:10.1155/2023/5541699
Natasha Nigar, Amna Wajid, S. A. Ajagbe, Matthew O. Adigun
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引用次数: 0

摘要

COVID-19 大流行影响了整个世界,改变了全球的社会生活。拉开社会距离是所有国家为防止人类受到感染而采取的有效策略。古兰经》是穆斯林的圣书,聆听和阅读《古兰经》是穆斯林的必修课之一。在传统的学习系统中,密切接触是必不可少的;然而,大多数古兰经学习学校都被封锁,以尽量减少 COVID-19 感染的传播。为了解决这一局限性,我们在本文中提出了一种新颖的系统,利用深度学习来识别《古兰经》中单个字母、诵读经文中的单词和完整经文的正确诵读,从而为诵读者提供帮助。此外,在建议的方法中,如果用户背诵正确,他/她的声音也会被添加到现有的数据集中,以提高建议方法的有效性。我们采用梅尔频率倒频谱系数(MFCC)来提取语音特征,并利用长短期记忆(LSTM)和循环神经网络(RNN)进行分类。上述方法使用《古兰经》数据集进行了验证。结果表明,所提出的系统优于最先进的方法,准确率高达 97.7%。该系统将帮助世界各地的穆斯林社区在未来类似的大流行病发生时,在没有人类帮助的情况下以正确的方式诵读《古兰经》。
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An Intelligent Framework Based on Deep Learning for Online Quran Learning during Pandemic
The COVID-19 pandemic influenced the whole world and changed social life globally. Social distancing is an effective strategy adopted by all countries to prevent humans from being infected. Al-Quran is the holy book of Muslims and its listening and reading is one of the obligatory activities. Close contact is essential in traditional learning system; however, most of the Al-Quran learning schools were locked down to minimize the spread of COVID-19 infection. To address this limitation, in this paper, we propose a novel system using deep learning to identify the correct recitation of individual alphabets, words from a recited verse and a complete verse of Al-Quran to assist the reciter. Moreover, in the proposed approach, if the user recites correctly, his/her voice is also added to the existing dataset to leverage proposed approach effectiveness. We employ mel-frequency cepstral coefficients (MFCC) to extract voice features and long short-term memory (LSTM), a recurrent neural network (RNN) for classification. The said approach is validated using the Al-Quran dataset. The results demonstrate that the proposed system outperforms the state-of-the-art approaches with an accuracy rate of 97.7%. This system will help the Muslim community all over the world to recite the Al-Quran in the right way in the absence of human help due to similar future pandemics.
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来源期刊
Applied Computational Intelligence and Soft Computing
Applied Computational Intelligence and Soft Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
6.10
自引率
3.40%
发文量
59
审稿时长
21 weeks
期刊介绍: Applied Computational Intelligence and Soft Computing will focus on the disciplines of computer science, engineering, and mathematics. The scope of the journal includes developing applications related to all aspects of natural and social sciences by employing the technologies of computational intelligence and soft computing. The new applications of using computational intelligence and soft computing are still in development. Although computational intelligence and soft computing are established fields, the new applications of using computational intelligence and soft computing can be regarded as an emerging field, which is the focus of this journal.
期刊最新文献
Performance Augmentation of Base Classifiers Using Adaptive Boosting Framework for Medical Datasets An Intelligent Framework Based on Deep Learning for Online Quran Learning during Pandemic Corrigendum to “An Efficient Blind Image Deblurring Using a Smoothing Function” Aspect-Based Sentiment Analysis for Afaan Oromoo Movie Reviews Using Machine Learning Techniques Applications of Quantum Probability Amplitude in Decision Support Systems
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