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Vocal acoustic analysis: ANN versos SVM in classification of dysphonic voices and vocal cords paralysis

dc.contributor.authorTeixeira, João Paulo
dc.contributor.authorAlves, Nuno Filipe Ribeiro
dc.contributor.authorFernandes, Paula Odete
dc.date.accessioned2020-04-23T08:54:43Z
dc.date.available2020-04-23T08:54:43Z
dc.date.issued2020
dc.description.abstractVocal acoustic analysis is becoming a useful tool for the classification and recognition of laryngological pathologies. This technique enables a non-invasive and low-cost assessment of voice disorders, allowing a more efficient, fast, and objective diagnosis. In this work, ANN and SVM were experimented on to classify between dysphonic/control and vocal cord paralysis/control. A vector was made up of 4 jitter parameters, 4 shimmer parameters, and a harmonic to noise ratio (HNR), determined from 3 different vowels at 3 different tones, with a total of 81 features. Variable selection and dimension reduction techniques such as hierarchical clustering, multilinear regression analysis and principal component analysis (PCA) was applied. The classification between dysphonic and control was made with an accuracy of 100% for female and male groups with ANN and SVM. For the classification between vocal cords paralysis and control an accuracy of 78,9% was achieved for female group with SVM, and 81,8% for the male group with ANN.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationTeixeira, João Paulo; Alves, Nuno; Fernandes, Paula O. (2020). Vocal acoustic analysis: ANN versos SVM in classification of dysphonic voices and vocal cords paralysis. International Journal of E-Health and Medical Communications (IJEHMC). ISSN 1947-315X. 11:1, p. 37-51pt_PT
dc.identifier.doi10.4018/IJEHMC.2020010103pt_PT
dc.identifier.eissn1947-3168
dc.identifier.issn1947-315X
dc.identifier.urihttp://hdl.handle.net/10198/21790
dc.language.isospapt_PT
dc.peerreviewedyespt_PT
dc.publisherIGI Globalpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectANNpt_PT
dc.subjectClassificationpt_PT
dc.subjectFeature selectionpt_PT
dc.subjectHierarchical clusteringpt_PT
dc.subjectHNRpt_PT
dc.subjectJitterpt_PT
dc.subjectMultilinear regression analysispt_PT
dc.subjectPCApt_PT
dc.subjectShimmerpt_PT
dc.subjectSVMpt_PT
dc.subjectVocal acoustic analysispt_PT
dc.subjectVoice pathologiespt_PT
dc.titleVocal acoustic analysis: ANN versos SVM in classification of dysphonic voices and vocal cords paralysispt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage51pt_PT
oaire.citation.issue1pt_PT
oaire.citation.startPage37pt_PT
oaire.citation.titleInternational Journal of E-Health and Medical Communicationspt_PT
oaire.citation.volume11pt_PT
person.familyNameTeixeira
person.familyNameFernandes
person.givenNameJoão Paulo
person.givenNamePaula Odete
person.identifier663194
person.identifierN-3804-2013
person.identifier.ciencia-id4F15-B322-59B4
person.identifier.ciencia-id991D-9D1E-D67D
person.identifier.orcid0000-0002-6679-5702
person.identifier.orcid0000-0001-8714-4901
person.identifier.ridN-6576-2013
person.identifier.scopus-author-id57069567500
person.identifier.scopus-author-id35200741800
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication33f4af65-7ddf-46f0-8b44-a7470a8ba2bf
relation.isAuthorOfPublication2269147c-2b53-4d1c-bc1b-f1367d197262
relation.isAuthorOfPublication.latestForDiscovery33f4af65-7ddf-46f0-8b44-a7470a8ba2bf

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