National Changhua University of Education Institutional Repository : Item 987654321/18359
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题名: Driver Identification Based on Voice Signal Using Continuous Wavelet Transform and Artificial Neural Network Techniques
作者: Wu, Jian-Da;Ye, Siou-Huan
贡献者: 車輛科技研究所
关键词: Speaker identification;Continuous wavelet transform;Artificial neural network
日期: 2009-03
上传时间: 2014-04-29T07:28:10Z
出版者: Elsevier Ltd
摘要: This paper presents a study of driver’s voice feature selection and classification for speaker identification in a vehicle security system. The proposed system consisted of a combination of feature extraction using continuous wavelet technique and voice classification using artificial neural network. In the feature extraction, a time-averaged wavelet spectrum based on continuous wavelet transform is proposed. Meanwhile, the artificial neural network techniques were used for classification in the proposed system. In order to verify the effect of the proposed system for classification, a conventional back-propagation neural network (BPNN) and generalized regression neural network (GRNN) were used and compared in the experimental investigation. The experimental results demonstrated the effectiveness of the proposed speaker identification system. The identification rate is about 92% for using BPNN and 97% for using GRNN approach.
關聯: Expert Systems with Applications, 36(2)Part1: 1061-1069
显示于类别:[車輛科技研究所] 期刊論文

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