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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics
Asti F. Fadlilah
Universitas Jenderal Achmad Yani
Computer Science & IT Electrical & Electronics Engineering

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Speaker and Speech Recognition Using Hierarchy Support Vector Machine and Backpropagation Asti F. Fadlilah; Esmeralda C. Djamal
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1969

Abstract

Voice signal processing has been proposed to improve effectiveness and facilitate the public, such as Smart Home. This study aims a smart home simulation model to move doors, TVs, and lights from voice instructions. Sound signals are processed using Mel-frequency Cepstrum Coefficients (MFCC) to perform feature extraction. Then, the voice is recognized by the speaker using a hierarchy Support Vector Machine (SVM). So that unregistered speakers are not processed or are declared not having access rights. For the process of recognizing spoken words such as "Open the Door”,"Close the Door","Turn on the TV","Turn off the TV","Turn on the Lights" and "Turn Offthe Lights" are done using Backpropagation. The results showed that hierarchy SVM provided an accuracy of 71% compared to the single SVM of 45%.
Co-Authors Esmeralda C. Djamal