Using PCA algorithm in voice recognition

dc.contributor.authorGorgunoglu, S.
dc.contributor.authorOzkaynak, E.
dc.contributor.authorOrak, I.M.
dc.date.accessioned2024-09-29T16:22:12Z
dc.date.available2024-09-29T16:22:12Z
dc.date.issued2012
dc.departmentKarabük Üniversitesien_US
dc.description.abstractVoice is a biometric feature that is used to distinguish or to identify human beings or species. Origin of the existing voice can be determined by analyzing the sound signal. Since voice of the human beings has disparities, it can be used for recognizing people. Various devices or machines are also controlled by voice commands obtained from the words out of the sound signal from one's speeches. In this study, Principal Component Analysis (PCA) algorithm which is mostly used in face recognition system is investigated for voice recognition purposes. PCA algorithm along with Support Vector Machines (SVMs) and K-means algorithms are realized for voice recognition and also their performances are compared. It is shown that PCA algorithm can be used as alternative to the well known voice recognition algorithms © Sila Science.en_US
dc.identifier.endpage764en_US
dc.identifier.issn1308-772X
dc.identifier.issueSPEC .ISS.1en_US
dc.identifier.scopus2-s2.0-84885048156en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage759en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9877
dc.identifier.volume30en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofEnergy Education Science and Technology Part A: Energy Science and Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectK-meansen_US
dc.subjectPrincipal component analysis (PCA)en_US
dc.subjectSupport vector machine (SVM)en_US
dc.subjectVoice processingen_US
dc.subjectVoice recognitionen_US
dc.titleUsing PCA algorithm in voice recognitionen_US
dc.typeArticleen_US

Dosyalar