Title :
Speech recognition - based control system for Drone
Author :
Supimros, Songpol ; Wongthanavasu, Sartra
Author_Institution :
Dept. of Comput. Sci., Khon Kaen Univ., Khon Kaen, Thailand
Abstract :
This project presents a speech-based control system for DRONE using Support Vector Machines (SVM). The set of controlling speeches consists of BACKWARD, FORWARD, HOLD ON, LANDING, MOVE UP, MOVE DOWN, TAKE OFF, TURN LEFT and TURN RIGHT are trained the SVM. The feature extraction of speech used in this study comprises of “fundamental frequency”, “Energy”, and Mel Frequency Cepstral Coefficient”. For performance evaluation, a set of features are used to test the SVM-based system developed by MATLAB. The results show that the average percentage of accuracy of the controlling speeches are 22.22, 46.67, 97.78 and 95.56 for fundamental frequency, energy, Mel frequency cepstral coefficient and all features, respectively. In addition, the interface of SVM-based system and DRONE is developed in practical use.
Keywords :
aerospace computing; autonomous aerial vehicles; cepstral analysis; feature extraction; speech recognition; support vector machines; Drone; MATLAB; Mel frequency cepstral coefficient; SVM; feature extraction; fundamental frequency; performance evaluation; speech recognition-based control system; support vector machines; unmanned aircraft parrot; Control systems; Feature extraction; Frequency control; Mel frequency cepstral coefficient; Speech; Support vector machines; Drone; speech recognition; support vector machines;
Conference_Titel :
Student Project Conference (ICT-ISPC), 2014 Third ICT International
Conference_Location :
Nakhon Pathom
Print_ISBN :
978-1-4799-5572-5
DOI :
10.1109/ICT-ISPC.2014.6923229
