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Nonperiodic pathologic voice signals classification using mel-spectrogram and VGGish

2025Documento de conferência Acesso aberto
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datacite.subject.fosEngenharia e Tecnologia
dc.contributor.authorFernandes, Joana
dc.contributor.authorPinto, João
dc.contributor.authorMoura, Carla
dc.contributor.authorVilarinho, Helena
dc.contributor.authorTeixeira, Felipe
dc.contributor.authorFreitas, D.
dc.contributor.authorTeixeira, João Paulo
dc.date.accessioned2026-05-18T16:22:00Z
dc.date.available2026-05-18T16:22:00Z
dc.date.issued2025
dc.description.abstractIn this work and the literature, voice signals can be classified as peri-odic (type 1) or either some periodicity (type 2) and chaos (type 3). This work aims to classify signs into types 1, 2 or 3 to be subsequently applied in a classifi-cation system for pathological/control signs. The original dataset is composed of 466 type 1 individuals, 900 type 2 individuals, and 84 type 3 individuals classi-fied by an otolaryngologist. 15% of the data was used for testing and the remain-ing 85% was used for training and validation. A data augmentation technique was applied to balance the data in training set. Therefore, for the test set, 3380 sounds were used, 1020 type 1, 1280 type 2 and 1080 type 3. Of these, 80% were used for training and 20% for validation. The Mel spectrograms of the signals were used in the input of a VGGish to retrain the model in classifying the 3 types of signals. Regarding test accuracy, this network obtained 71.2%.por
dc.description.sponsorshipThis work was supported by national funds through FCT/MCTES (PIDDAC): CeDRI, UIDB/05757/2020 (DOI: 10.54499/UIDB/05757/2020) and UIDP/05757/2020 (DOI: 10.54499/UIDP/05757/2020); and SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020) and 2021.04729.BD (DOI: 10.54499/2021.04729.BD).
dc.identifier.citationFernandes, Joana; Pinto, João; Moura, Carla; Vilarinho, Helena; Teixeira, Felipe; Freitas, D.; Teixeira, João Paulo (2025) Nonperiodic pathologic voice signals classification using mel-spectrogram and VGGish. In International Conference on Demographic Transition, Health and Technologies, ICDTHT 2025. p. 3-13. ISBN 978-303194900-5. DOI: 10.1007/978-3-031-94901-2_1
dc.identifier.doi10.1007/978-3-031-94901-2_1
dc.identifier.isbn978-303194900-5
dc.identifier.urihttp://hdl.handle.net/10198/36722
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature Switzerland
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
dc.relation.ispartofSpringer Proceedings in Business and Economics
dc.relation.ispartofHealth Technologies and Demographic Challenges
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleNonperiodic pathologic voice signals classification using mel-spectrogram and VGGishpor
dc.typeconference object
dspace.entity.typePublication
oaire.awardNumberUIDB/05757/2020
oaire.awardNumberLA/P/0007/2020
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.citation.endPage13
oaire.citation.startPage3
oaire.citation.titleInternational Conference on Demographic Transition, Health and Technologies, ICDTHT 2025
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_b1a7d7d4d402bcce
person.familyNameTeixeira
person.familyNameTeixeira
person.givenNameFelipe
person.givenNameJoão Paulo
person.identifier663194
person.identifier.ciencia-id0E17-62FB-AA17
person.identifier.ciencia-id4F15-B322-59B4
person.identifier.orcid0000-0002-6679-5702
person.identifier.ridN-6576-2013
person.identifier.scopus-author-id57069567500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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