Linear prediction and discrete wavelet transform to identify pathology in voice signals

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dc.contributor.authorFonseca, Everthon Silva [UNESP]
dc.contributor.authorPereira, Denis Cesar Mosconi
dc.contributor.authorMaschi, Luis Fernando Castilho
dc.contributor.authorGuido, Rodrigo Capobianco [UNESP]
dc.contributor.authorPaulo, Katia Cristina Silva [UNESP]
dc.contributor.institutionFederal Institute of São Paulo (IFSP)
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T17:34:56Z
dc.date.available2018-12-11T17:34:56Z
dc.date.issued2017-09-28
dc.description.abstractThis work describes an algorithm to help in the identification of pathologically affected voices. Based on inverse linear prediction filter (LPC) and discrete wavelet transform (DWT), this method can be used in conjunction with other classifiers in order to improve them, by the addition of the new parameter we propose, DWT-RMS. Using no association with other methods, DWT-RMS gives quantitative evaluation of voice signals from male and female subjects of different ages and leads to an adequate larynx pathology classifier with 85.94% of classification accuracy, 0% of false negatives and 14.06% of false positives, to identify nodules in vocal folds.en
dc.description.affiliationIndustry Department Federal Institute of São Paulo (IFSP)
dc.description.affiliationInstitute of Biosciences Sao Paulo State University (UNESP)
dc.description.affiliationUnespInstitute of Biosciences Sao Paulo State University (UNESP)
dc.identifierhttp://dx.doi.org/10.1109/SPS.2017.8053638
dc.identifier.citation2017 Signal Processing Symposium, SPSympo 2017.
dc.identifier.doi10.1109/SPS.2017.8053638
dc.identifier.lattes6542086226808067
dc.identifier.orcid0000-0002-0924-8024
dc.identifier.scopus2-s2.0-85034750369
dc.identifier.urihttp://hdl.handle.net/11449/179379
dc.language.isoeng
dc.relation.ispartof2017 Signal Processing Symposium, SPSympo 2017
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectpathologies
dc.subjectprediction
dc.subjectsignals
dc.subjectvoice
dc.subjectwavelet
dc.titleLinear prediction and discrete wavelet transform to identify pathology in voice signalsen
dc.typeTrabalho apresentado em evento
unesp.author.lattes6542086226808067[4]
unesp.author.orcid0000-0002-0924-8024[4]

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Artigos - Ciência da Computação e Estatística - IBILCE