基于卷积神经网络的智能家居方言密码识别

Ming Zhang, Cuiyun Gao, Siqiang Xu
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引用次数: 0

摘要

目前,智能家居中的密码识别已经取得了一定的研究成果,但由于中国地区差异较大,智能家居中的方言密码识别率较低。针对智能家居方言密码识别存在的缺陷,构建了基于卷积神经网络的方言密码识别系统。本研究采用Mel频率倒谱系数提取安徽北部方言特征,构建卷积神经网络模型进行训练和识别。实验结果表明,该模型对智能家居中的方言密码具有较高的识别率。
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Dialect Password Recognition In Smart Home Based On Convolutional Neural Network
At present, password recognition in smart home has achieved some research results, but due to the relatively large China's regional differences, dialect password recognition rate in smart home is low. Aiming at the defects of dialect password recognition in smart home, a dialect password recognition system based on Convolutional Neural Network was constructed. In this study, Mel Frequency Cepstrum Coefficient is used to extract the features of Anhui northern dialect, and a Convolutional Neural Network model is constructed for training and recognition. Experimental results show that the model has a high recognition rate for dialect passwords in smart home.
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