Comparative Evaluation of MFCC and Mel-spectrogram Features for CNN-Based Respiratory Abnormality Detection

Automated respiratory sound analysis addresses critical limitations in traditional clinical auscultation, particularly high inter-observer variability and limited specialist access in resource-constrained settings. This study rigorously compares Mel-Frequency Cepstral Coefficients (MFCC) and Mel-spe...

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Principais autores:	Simboni Simboni Tege, Kafunda Katalay Pierre, Oshasha Oshasha Fiston, Sylvestre Frey, Albert Ntumba Nkongolo, Biaba Kuya Jirince
Format:	Artigo
Jezik:	Inglês
Izdano:	Politeknik Negeri Batam 2026-04-01
Serija:	Journal of Applied Informatics and Computing
Teme:	convolutional neural networks (cnns) respiratory sounds mfcc mel-spectrogram medical diagnosis
Online dostop:	https://jurnal.polibatam.ac.id/index.php/JAIC/article/view/12355
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