Control of robot arm based on speech recognition using Mel-Frequency Cepstrum Coefficients (MFCC) and K-Nearest Neighbors (KNN) method

Abstract

In this study describe the implementation of speech recognition to pick and place an object using 5 DoF Robot Arm based on Arduino Microcontroller. To identify the speech used Mel-Frequency Cepstrum Coefficients (MFCC) method to get feature extraction and K-Nearest Neighbors (KNN) method to learn and identify the speech recognition based on Python 2.7. The database of speech use 12 feature for KNN process, then tested using trained (85%) and not trained (80%) respondent show the best agreement result to identifying the speech recognition. Finally, the speech recognition system implemented to control Robot Arm for perform assignment pick and place the object.