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Design of a text ındependent speaker recognition system

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dc.contributor.author Özaydın, Selma
dc.date.accessioned 2020-03-19T12:47:55Z
dc.date.available 2020-03-19T12:47:55Z
dc.date.issued 2017
dc.identifier.citation Özaydın, Selma, "Design of a text ındependent speaker recognition system", 2017 International Conference On Electrical And Computing Technologies And Applications (ICECTA), pp.55-59, (2017). tr_TR
dc.identifier.isbn 978-1-5386-0872-2
dc.identifier.uri http://hdl.handle.net/20.500.12416/2698
dc.description.abstract This paper presents the design of a text independent speaker recognition system based on Mel-Frequency Cepstrum Coefficients and Gaussian Mixture Models. HTK speech recognition toolkit is used in the design of speaker models. The system is aimed to use it as a biometric authentication system. The experiments were performed on speech data consist of 134 speakers from YOHO database for different training conditions. The increase of the proposed system performance is observed with the decrease of Equal Error Rate. Experiment results show that the system gives the best recognition performance for Gaussian mixture model with 64 mixtures. tr_TR
dc.language.iso eng tr_TR
dc.publisher IEEE tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Speaker Recognition tr_TR
dc.subject Voice Recognition tr_TR
dc.subject Gaussian Mixture Model tr_TR
dc.subject Biometrics tr_TR
dc.subject HTK tr_TR
dc.title Design of a text ındependent speaker recognition system tr_TR
dc.type conferenceObject tr_TR
dc.relation.journal 2017 International Conference On Electrical And Computing Technologies And Applications (ICECTA) tr_TR
dc.contributor.authorID 253019 tr_TR
dc.identifier.startpage 55 tr_TR
dc.identifier.endpage 59 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Elektronik ve Haberleşme Mühendisliği Bölümü tr_TR


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