Automatic Multiclass Classification of Voice Disorders Using Cochlear-Inspired Cepstral Features and Deep Learning Networks

Lotfi Salhi, Mariem Gammoudi, Ridha ben Salah

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DOI: 10.1016/j.jvoice.2026.10.057
Published: 2026-11
Container: Journal of Voice
Publisher: Elsevier BV
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1016/j.jvoice.2026.10.057,
  title = {Automatic Multiclass Classification of Voice Disorders Using Cochlear-Inspired Cepstral Features and Deep Learning Networks},
  author = {Lotfi Salhi and Mariem Gammoudi and Ridha ben Salah},
  year = {2026},
  journal = {Journal of Voice},
  doi = {10.1016/j.jvoice.2026.10.057},
  url = {https://doi.org/10.1016/j.jvoice.2026.10.057}
}

RIS

TY  - JOUR
TI  - Automatic Multiclass Classification of Voice Disorders Using Cochlear-Inspired Cepstral Features and Deep Learning Networks
AU  - Lotfi Salhi
AU  - Mariem Gammoudi
AU  - Ridha ben Salah
PY  - 2026
JO  - Journal of Voice
DO  - 10.1016/j.jvoice.2026.10.057
UR  - https://doi.org/10.1016/j.jvoice.2026.10.057
ER  -

APA

Salhi, L., Gammoudi, M., & Salah, R. B. (2026). Automatic Multiclass Classification of Voice Disorders Using Cochlear-Inspired Cepstral Features and Deep Learning Networks. Journal of Voice. https://doi.org/10.1016/j.jvoice.2026.10.057

Source records

crossref · retrieved 2026-11-09T04:33:16.542Z