A new feature constituting approach to detection of vocal fold pathology

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dc.authorid0000-0002-8929-3473en_US
dc.authorid0000-0003-1840-9958en_US
dc.contributor.authorHariharan, Muthusamy
dc.contributor.authorPolat, Kemal
dc.contributor.authorYaacob, Sazali
dc.date.accessioned2021-06-23T19:36:46Z
dc.date.available2021-06-23T19:36:46Z
dc.date.issued2014
dc.departmentBAİBÜ, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description.abstractIn the last two decades, non-invasive methods through acoustic analysis of voice signal have been proved to be excellent and reliable tool to diagnose vocal fold pathologies. This paper proposes a new feature vector based on the wavelet packet transform and singular value decomposition for the detection of vocal fold pathology. k-means clustering based feature weighting is proposed to increase the distinguishing performance of the proposed features. In this work, two databases Massachusetts Eye and Ear Infirmary (MEEI) voice disorders database and MAPACI speech pathology database are used. Four different supervised classifiers such as k-nearest neighbour (k-NN), least-square support vector machine, probabilistic neural network and general regression neural network are employed for testing the proposed features. The experimental results uncover that the proposed features give very promising classification accuracy of 100% for both MEEI database and MAPACI speech pathology database.en_US
dc.identifier.doi10.1080/00207721.2013.794905
dc.identifier.endpage1634en_US
dc.identifier.issn0020-7721
dc.identifier.issn1464-5319
dc.identifier.issue8en_US
dc.identifier.scopus2-s2.0-84902775189en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1622en_US
dc.identifier.urihttps://doi.org/10.1080/00207721.2013.794905
dc.identifier.urihttps://hdl.handle.net/20.500.12491/8051
dc.identifier.volume45en_US
dc.identifier.wosWOS:000337363600002en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorPolat, Kemal
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofInternational Journal Of Systems Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAcoustic Analysisen_US
dc.subjectVocal Fold Pathologyen_US
dc.subjectFeature Extractionen_US
dc.subjectFeature Weighting and Classificationen_US
dc.titleA new feature constituting approach to detection of vocal fold pathologyen_US
dc.typeArticleen_US

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