Ensemble MLP networks for voices command classification to control model car via piFace interface of raspberry Pi

• Main Authors: Eiamkanitchat N., Kuntekul N., Panyaphruek P.
• Format: Journal
• Published: 2017
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85018735994&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/40939
• Institution: Chiang Mai University

© Int. J. of GEOMATE. This research, exploration displays the aftereffects of utilizing the blend of the multi-layer perceptron network system to classify Thai speech. The parameters of the training process are used in the mobile application to using Thai voice commands to control the model car. The PiFace interface of the Raspberry Pi is attached to the model car for receiving the command from mobile and control the model car. The 1,000 Thai voice commands of both men and ladies are used as the training set in the experiment. The preliminary experiments have been done to find the best possible structure of the classification model, and the appropriate proportion of classes in the training set. From the experiment results using 1 network for one voice command, the average accuracy of the classification results in the environment without noise is higher than 80%, which considered favorable in the speech recognition field of study.