Motorcycle Start-stop System based on Intelligent Biometric Voice Recognition

2016 2nd International Conference on Mechanical and Aeronautical Engineering (ICMAE 2016)

机械制造;航空航天工程

Winda, A.^1 ; Byan, W.R.E.^2 ; Sofyan, S.^1 ; Armansyah, A.^2 ; Zariantin, D.L.^3 ; Josep, B.G.^4

Computer Engineering, Bina Nusantara University, Indonesia^1

Industrial Engineering, Bina Nusantara University, Indonesia^2

Mechanical Engineering, Pancasila University, Indonesia^3

School of Computer Science, Bina Nusantara University, Indonesia^4

关键词: Biometric voice;    False acceptance rate;    False rejection rate;    Feature extraction techniques;    Intelligent word recognition;    Mel frequencies;    Training and testing;    Word recognition;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/187/1/012039/pdf
DOI  :  10.1088/1757-899X/187/1/012039

学科分类：航空航天科学

来源: IOP

【 摘 要 】

Current mechanical key in the motorcycle is prone to bulgary, being stolen or misplaced. Intelligent biometric voice recognition as means to replace this mechanism is proposed as an alternative. The proposed system will decide whether the voice is belong to the user or not and the word utter by the user is 'On' or 'Off'. The decision voice will be sent to Arduino in order to start or stop the engine. The recorded voice is processed in order to get some features which later be used as input to the proposed system. The Mel-Frequency Ceptral Coefficient (MFCC) is adopted as a feature extraction technique. The extracted feature is the used as input to the SVM-based identifier. Experimental results confirm the effectiveness of the proposed intelligent voice recognition and word recognition system. It show that the proposed method produces a good training and testing accuracy, 99.31% and 99.43%, respectively. Moreover, the proposed system shows the performance of false rejection rate (FRR) and false acceptance rate (FAR) accuracy of 0.18% and 17.58%, respectively. In the intelligent word recognition shows that the training and testing accuracy are 100% and 96.3%, respectively.