Anggraeni, D and Sanjaya WS, Mada and Nurasyidiek, M Y S and Munawwaroh, M (2017) 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: The 2nd Annual Applied Science and Engineering Conference (AASEC 2017), 24 August 2017, Bandung.
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Text (The Implementation of Speech Recognition using Mel-Frequency Cepstrum Coefficients (MFCC) and Support Vector Machine (SVM) method based on Python to Control Robot Arm)
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Abstract
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.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Applied Physics Applied Physics > Security, Sound Recording Other Branches of Engineering Other Branches of Engineering > Automatic Control Engineering |
| Divisions: | Fakultas Sains dan Teknologi > Program Studi Fisika |
| Depositing User: | Mada Sanjaya W. S. |
| Date Deposited: | 21 Aug 2018 19:20 |
| Last Modified: | 21 Aug 2018 19:20 |
| URI: | https://etheses.uinsgd.ac.id/id/eprint/11619 |
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