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Evaluation of Quran Recitation via OWL Ontology Based System

机译:通过基于OWL本体的系统评估古兰经背诵

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The Linguistic miracle in the Holy Quran leads to many challenges in Automate Quran recitation evaluation. This paper considers one of suggestions of how natural language processing can benefit from using ontology. In this paper, we proposed a general automatic system to evaluate Quran recitation according to Hafs reading. That is via integration the ontology based as artificial intelligent knowledge representation method and Automatic Speech Recognition (ASR) technology as a way of interaction with computer. Our proposed system solves the problem of evaluating all intonations (Tajweed) in the same time in addition to evaluate set of Quran segments in the wright arrangement of reading. The system uses Mel-Frequency Cepsfral Coefficients (MFCC) and Vector Quantization (VQ) respectively in feature extraction and dimension reduction on Arabic speech. Also, we construct Quran ontology based for Quranic speech and integrate it with information refrieval system. Quran ontology based is the first version to merge Quran meaning "Tafseer" and its recitation in the Universal oral exam to take advantage of semantic property of ontology. Experimentally, our system gives good accuracy for Quran recitation evaluation.
机译:《古兰经》中的语言奇迹给《古兰经》自动化朗诵评估带来了许多挑战。本文考虑了自然语言处理如何从使用本体中受益的建议之一。在本文中,我们提出了一种通用的自动系统,可根据Hafs阅读来评估古兰经的朗诵。即通过集成基于本体的人工智能知识表示方法和与计算机交互的自动语音识别(ASR)技术。我们提出的系统解决了同时评估所有语调(Tajweed)的问题,此外还评估了阅读者赖特排列中的古兰经片段集。该系统分别使用Mel-频率倒谱系数(MFCC)和矢量量化(VQ)进行阿拉伯语语音的特征提取和降维。此外,我们基于古兰经语音构建古兰经本体,并将其与信息检索系统集成。基于古兰经本体的版本是第一个合并古兰经的版本,意为“ Tafseer”及其通用考试中的口述,以利用本体的语义特性。在实验上,我们的系统为古兰经背诵评估提供了良好的准确性。

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