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Detection of Laryngeal Pathologies from Voice using EMD-based Mel-Spectrograms and Scalograms with AlexNet Cover

Detection of Laryngeal Pathologies from Voice using EMD-based Mel-Spectrograms and Scalograms with AlexNet

Measurement Science Review
Volume 25 (2025): Issue 5 (October 2025)
By: Sofiane Cherif,  Abdelhafid Kaddour,  Abdelmoudjib Benkada and  Said Karoui  
Open Access
|Oct 2025

Authors

Sofiane Cherif

sofiane.cherif@univ-usto.dz

Signals, Systems, and Data Laboratory (LSSD), Electronics Department, Faculty of Electrical Engineering, University of Sciences and Technology of Oran Mohamed Boudiaf (USTO MB), Oran, Algeria

Abdelhafid Kaddour

Signals, Systems, and Data Laboratory (LSSD), Electronics Department, Faculty of Electrical Engineering, University of Sciences and Technology of Oran Mohamed Boudiaf (USTO MB), Oran, Algeria

Abdelmoudjib Benkada

Signals, Systems, and Data Laboratory (LSSD), Electronics Department, Faculty of Electrical Engineering, University of Sciences and Technology of Oran Mohamed Boudiaf (USTO MB), Oran, Algeria

Said Karoui

Signals, Systems, and Data Laboratory (LSSD), Electronics Department, Faculty of Electrical Engineering, University of Sciences and Technology of Oran Mohamed Boudiaf (USTO MB), Oran, Algeria
DOI: https://doi.org/10.2478/msr-2025-0030 | Journal eISSN: 1335-8871
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Language: English
Page range: 276 - 283
Submitted on: Oct 21, 2024
|
Accepted on: Aug 28, 2025
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Published on: Oct 15, 2025
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
laryngeal pathology detection,
voice signal processing,
empirical mode decomposition,
Mel-spectrogram,
scalogram,
AlexNet convolutional neural network
Related subjects:
Engineering,
Electrical engineering,
Control engineering, metrology and testing

© 2025 Sofiane Cherif, Abdelhafid Kaddour, Abdelmoudjib Benkada, Said Karoui, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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