Implementation of Dysarthria Identification Using MFCC and Multilayer Perceptron Algorithm

International Journal of Electrical and Electronics Engineering

© 2025 by SSRG - IJEEE Journal

Volume 12 Issue 1

Year of Publication : 2025

Authors : Abdul Fadlil, Latief Perdana, Ardi Pujiyanta, Herman, Haris Imam Karim Fathurrahman, Maulana Muhammad Jogo Samodro

10.14445/23488379/IJEEE-V12I1P105

How to Cite?

Abdul Fadlil, Latief Perdana, Ardi Pujiyanta, Herman, Haris Imam Karim Fathurrahman, Maulana Muhammad Jogo Samodro, "Implementation of Dysarthria Identification Using MFCC and Multilayer Perceptron Algorithm," SSRG International Journal of Electrical and Electronics Engineering, vol. 12,  no. 1, pp. 32-46, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I1P105

Abstract:

Dysarthria is an inability of the child’s muscles to pronounce certain vocabulary. One of the words that is often difficult to pronounce is the R sound. Therefore, it is important to identify R sound dysarthria as a preventive measure and can be used as a therapeutic reference. The study uses the phrase “laler menclok pager” as the basis for picking up voice data in children. In that sentence, there is a letter R that will be processed later. The processing method used is MFCC. The output from the extraction of the MFCC characteristics is inserted as the input material of the Multilayer Perceptron (MLP) artificial intelligence algorithm. The results of this study provide a high degree of accuracy, and the test data can be well identified as a whole. The results also obtained the MLP configuration of 16 input neurons and 8 hidden neurons with the highest accuracy as well as the lightest computing. With this result, further hardware can be developed to integrate the system for identifying dysarthria.

Keywords:

Dysarthria, MFCC, MLP, Neuron, R sound.

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