Arabic word dependent speaker identification system using artificial neural network

被引：0

作者：

Al-Qaisi, Aws ^{[1
]}

机构：

[1] Communication Engineering Department, Faculty of Engineering Technology, Al-Balqa Applied University, Jordan

来源：

International Journal of Circuits, Systems and Signal Processing | 2020年 / 14卷

关键词：

Loudspeakers - Speech recognition - Radial basis function networks - Signal to noise ratio;

D O I：

10.46300/9106.2020.14.41

中图分类号：

学科分类号：

摘要：

The security of systems is a vital issue for any society. Hence, the need for authentication mechanisms that protect the confidentiality of users is important. This paper proposes a speech based security system that is able to identify Arabic speakers by using an Arabic word)اركش) which means Thank you. The pre-processing steps are performed on the speech signals to enhance the signal to noise ratio. Features of speakers are obtained as Mel-Frequency Cepstral Coefficients (MFCC). Moreover, feature selection (FS) and radial basis function neural network (RBFNN) are implemented to classify and identify speakers. The proposed security system gives a 97.5% accuracy rate in its user identification process. © 2020, North Atlantic University Union. All rights reserved.

引用

页码：290 / 295

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