The Implementation of Speech Recognition using Mel-Frequency Cepstrum Coefficients (MFCC) and Support Vector Machine (SVM) method based on Python to Control Robot Arm

In this paper describe an implementation of speech recognition to pick and place an object using Robot Arm. To get the feature extraction of speech signal used Mel-Frequency Cepstrum Coefficients (MFCC) method and to learn the database of speech recognition used Support Vector Machine (SVM) method,...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2018-01, Vol.288 (1), p.12042
Main Authors: Anggraeni, D, Sanjaya, W S M, Nurasyidiek, M Y S, Munawwaroh, M
Format: Article
Language:English
Subjects:
Algorithms
Feature extraction
Machine learning
Microcontrollers
Object recognition
Robot arms
Robot control
Robots
Speech
Speech recognition
Support vector machines
Voice recognition
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Summary:In this paper describe an implementation of speech recognition to pick and place an object using Robot Arm. To get the feature extraction of speech signal used Mel-Frequency Cepstrum Coefficients (MFCC) method and to learn the database of speech recognition used Support Vector Machine (SVM) method, the algorithm based on Python 2.7. The data learning which used to SVM process are 12 features, then the system tested using trained and not trained data show the best agreement to identifying the speech recognition. The speech recognition system has been implemented for control the 5 DoF Robot Arm based Arduino microcontroller to doing task pick and place the object.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/288/1/012042