Determining efficiency of speech feature groups in emotion detection

Basit Öğe Kaydı
dc.authorid0000-0002-2126-8757
dc.contributor.authorPolat, Goekhan
dc.contributor.authorAltun, Halis
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2007
dc.departmentNiğde ÖHÜ
dc.descriptionIEEE 15th Signal Processing and Communications Applications Conference -- JUN 11-13, 2007 -- Eskisehir, TURKEY
dc.description.abstractFeatures, extract from speech parameter are frequently used in emotion detection problem. Prosodic, MFCC, LPC and band energy feature groups are commonly used in literature to detect emotion in speech. The aim of the study is to examine the efficiency of these features groups in emotion detection problem using a SVM classifier.
dc.description.sponsorshipIEEE
dc.identifier.endpage+
dc.identifier.isbn978-1-4244-0719-4
dc.identifier.scopus2-s2.0-50249117767
dc.identifier.scopusqualityN/A
dc.identifier.startpage463
dc.identifier.urihttps://hdl.handle.net/11480/5422
dc.identifier.wosWOS:000252924600116
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2007 IEEE 15TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS, VOLS 1-3
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titleDetermining efficiency of speech feature groups in emotion detection
dc.typeConference Object

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu