A Study on Turkish Text - Dependent Speaker Recognition

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dc.contributor.authorÇeliktaş, Havva
dc.contributor.authorHanilçi, Cemal
dc.date.accessioned2021-03-20T20:14:08Z
dc.date.available2021-03-20T20:14:08Z
dc.date.issued2017
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEYen_US
dc.description.abstractSpeaker recognition is a pattern recognition task which has long been studied, but the accuracies are still far from the desired levels. The majority of the studies on speaker recognition demonstrates the results obtained from databases in which English voices are used. Since there are very few studies on Turkish speech, the performance of the known successful methods in Turkish voices are uncertain. Therefore, in this study, the performance on the Turkish text - dependent system is investigated by using Gaussian Mixture Model - Universal Background Model (GMM - UBM) method which is a well known method in speaker recognition systems. In the experimental studies, Turkish speaker recognition database consisting of 46 speakers (36 males and 10 females) is used. Equal error rate (EER) is used to measure system performance. The equal error rate for GMM - UBM method was found to be 5.73%. It has been observed in the experiments that the speaker verification performance of GMM - UBM classifier on Turkish database is encouraging.en_US
dc.description.sponsorshipTurk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univen_US
dc.identifier.isbn978-1-5090-6494-6
dc.identifier.issn2165-0608
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/20.500.12885/1001
dc.identifier.wosWOS:000413813100168en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorÇeliktaş, Havva
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2017 25Th Signal Processing And Communications Applications Conference (Siu)en_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectspeaker recognitionen_US
dc.subjectgaussian mixture modelen_US
dc.subjectuniversal background modelen_US
dc.subjectmel - frequency cepstral coefficientsen_US
dc.titleA Study on Turkish Text - Dependent Speaker Recognitionen_US
dc.typeConference Objecten_US

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