Comparison of Machine Learning Algorithms on Classification of Covid-19 Cough Sounds Using MFCC Extraction-Reference-Cited by-同舟云学术

Comparison of Machine Learning Algorithms on Classification of Covid-19 Cough Sounds Using MFCC Extraction

Published:2023-12-29 Issue: Volume:29 Page:399-404
ISSN:2544-0764
Container-title:Journal of Computer Sciences Institute
language:
Short-container-title:J. Comput. Sci. Inst.

Author:

Faisal Mohammad Reza,Hidayat Muhammad Thoriq,Kartini Dwi,Indriani Fatma,Budiman Irwan,Saragih Triando Hamonangan

Abstract

Early detection for COVID-19 has now been widely developed. One of the methods used is cough audio detection. This research aims to classify cough audio. Audio feature extraction is performed using MFCC to obtain numerical features. Feature classification is done using SVM, Random Forest, and Naive Bayes methods. Evaluation is done to find the best classification method. The evaluation results in this study show that SVM Kernel RBF produces the best evaluation value with an AUC value of 0.657715.

Publisher

Politechnika Lubelska

Subject

General Medicine

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