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Spoken Arabic Digits Recognition Based on (GMM) for E-Quran Voice Browsing: Application for Blind Category

机译:基于(GMM)的阿拉伯语数字语音识别古兰经语音浏览:盲目应用

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摘要

People with low or no visual ability must also be able to manipulate, operate and browse the electronic reading devices of the Quran by a simple use of the voice (operation known as Voice-In/Voice-Out). The main operations of navigation and exploration of these devices, as the movement between verses or between pages can be fully realized through a voice recognition system of Arabic numbers. In this paper, we propose the use of voice recognition of Arabic digits as a way to use these devices, for this purpose, we present the method of speech recognition based on: (GMM) classifier, known for its effectiveness and scalability in speech modeling and the leading approach in speech recognition feature extraction Delta-Delta Mel-frequency cepstral coefficients (MFCC). The experimental results with the obtained parameters demonstrate the effectiveness of the digit recognition on a dataset in 99.31% of cases, which is highly satisfactory compared to previous works on spoken Arabic digits speech recognition.
机译:视力较弱或没有视觉能力的人还必须能够通过简单地使用语音(称为语音输入/语音输出)来操纵,操作和浏览古兰经的电子阅读设备。这些设备的导航和浏览的主要操作(如经文之间或页面之间的移动)可以通过阿拉伯数字的语音识别系统完全实现。在本文中,我们建议使用阿拉伯数字的语音识别作为使用这些设备的一种方式,为此,我们提出了一种基于(GMM)分类器的语音识别方法,该分类器以其在语音建模中的有效性和可扩展性而闻名语音识别特征提取中的领先方法Delta-Delta Mel频率倒谱系数(MFCC)。使用获得的参数进行的实验结果证明了在99.31%的情况下在数据集上进行数字识别的有效性,与先前有关口头阿拉伯数字语音识别的工作相比,这是非常令人满意的。

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