Features and Classifiers for Replay Spoofing Attack Detection

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dc.authorid0000-0002-9174-0367en_US
dc.contributor.authorHanilçi, Cemal
dc.date.accessioned2021-03-20T20:14:02Z
dc.date.available2021-03-20T20:14:02Z
dc.date.issued2017
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.description10th International Conference on Electrical and Electronics Engineering (ELECO) -- NOV 30-DEC 02, 2017 -- Bursa, TURKEYen_US
dc.description.abstractAutomatic speaker verification (ASV) systems are known to be highly vulnerable against spoofing attacks. Various successful countermeasures have recently been proposed to detect spoofing attacks originating from speech synthesis (SS) and voice conversion (VC). However, detecting replay attacks, the most easily implementable spoofing attacks against ASV systems, has gained less attention. Thus, in this paper we present an experimental comparison of various feature extraction techniques and classifiers for replay attack detection. In total, six magnitude spectrum and three phase spectrum based features are used for feature extraction. For classification in turn, four different techniques are utilized. Experiments are conducted on recently released ASVspoof 2017 replay attack detection challenge. Experimental results reveals that magnitude spectrum features considerably outperform phase based features independent of the classifier. Comparative results using four different classifiers indicate that i-vector cosine scoring yields lower equal error rates (EERs) than other methods.en_US
dc.description.sponsorshipChamber Elect Engineers Bursa Branch, Uludag Univ, Fac Engn, Dept Elect & Elect Engn, Istanbul Tech Univ, Fac Elect & Elect Engn, Sci & Technolog Res Council Turkey, IEEE Turkey Secten_US
dc.description.sponsorshipBursa Technical UniversityBursa Technical University [2016-01-012]en_US
dc.description.sponsorshipThis work was supported by the Bursa Technical University under project no. 2016-01-012en_US
dc.identifier.endpage1191en_US
dc.identifier.isbn978-1-5386-1723-6
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1187en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12885/983
dc.identifier.wosWOS:000426978800209en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorHanilçi, Cemal
dc.language.isoenen_US
dc.publisherIeeeen_US
dc.relation.ispartof2017 10Th International Conference On Electrical And Electronics Engineering (Eleco)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject[No Keywords]en_US
dc.titleFeatures and Classifiers for Replay Spoofing Attack Detectionen_US
dc.typeConference Objecten_US

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