基于语音识别的无人机控制系统

Songpol Supimros, S. Wongthanavasu
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引用次数: 6

摘要

本课题提出了一种基于支持向量机(SVM)的无人机语音控制系统。由后退、前进、保持、着陆、上升、下降、起飞、左转、右转组成的控制语音集,通过SVM进行训练。本研究中使用的语音特征提取包括“基频”、“能量”和Mel频率倒谱系数。为了进行性能评价,采用一组特征对MATLAB开发的基于支持向量机的系统进行了测试。结果表明,控制语音在基频、能量、Mel频率倒谱系数和所有特征上的平均正确率分别为22.22、46.67、97.78和95.56。此外,还在实际应用中开发了基于svm的系统与无人机的接口。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speech recognition - based control system for Drone
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.
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