Mohammad Shahrul Izham Sharifuddin, Sharifalillah Nordin, A. Ali
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引用次数: 11
摘要
本文介绍了一种基于卷积神经网络(cnn)的语音控制智能轮椅运动。这款智能轮椅使用“停”、“走”、“左”、“右”等四种语音指令来帮助残疾人移动。数据以wav格式从google收集。使用Mel-Frequency倒谱系数(MFCC)提取命令语音。部署系统的硬件为Raspberry PI 3B+。该方法利用cnn对语音命令进行分类,准确率达到95.30%,取得了优异的效果。因此,该方法可以商业化,并有望为残疾人社会带来好处。
Voice Control Intelligent Wheelchair Movement Using CNNs
In this paper, we introduced a voice control intelligent wheelchair movement using Convolutional Neural Networks (CNNs). The intelligent wheelchair used four voice commands such as stop, go, left and right to assist disable people to move. Data are collected from google in the wav format. Mel-Frequency Cepstral Coefficient (MFCC) is applied to extract the command voice. The hardware used to deploy the system is Raspberry PI 3B+. The proposed method is using CNNs to classify the voice command and achieved excellent result with 95.30% accuracy. Therefore, the method can be commercialized and hopefully can give benefit to the disable society.