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dc.contributor.authorMporas, Iosif
dc.contributor.authorGanchev, Todor
dc.contributor.authorSiafarikas, Mihalis
dc.contributor.authorStoyanova, Tsenka
dc.date.accessioned2017-09-14T16:45:36Z
dc.date.available2017-09-14T16:45:36Z
dc.date.issued2014-03-31
dc.identifier.citationMporas , I , Ganchev , T , Siafarikas , M & Stoyanova , T 2014 , ' Wavelet basis selection for enhanced speech parametrization in speaker verification ' , International Journal of Speech Technology , vol. 17 , no. 1 , pp. 27-36 . https://doi.org/10.1007/s10772-013-9202-8
dc.identifier.issn1381-2416
dc.identifier.otherPURE: 10687923
dc.identifier.otherPURE UUID: 5b43c112-83f8-4848-b099-6d24dd2912dc
dc.identifier.otherScopus: 84895063111
dc.identifier.urihttp://hdl.handle.net/2299/19408
dc.descriptionTodor Ganchev, Mihalis Siafarikas, Iosif Mporas, and Tsenka Stoyanova, 'Wavelet basis selection for enhanced speech parametrization in speaker verification', International Journal of Speech Technology, vol. 17 (1): 27-36, June 2013, doi: https://doi.org/10.1007/s10772-013-9202-8. Published by Springer US.
dc.description.abstractWe study the inherent properties of nine wavelet functions and subsequently evaluate their applicability as basis functions in a speech parametrization scheme that is advantageous for speaker verification. Particularly, the inherent properties of nine candidate basis functions are initially analysed and their advantages and disadvantages are discussed. Subsequently, all candidates are employed in a well-proven speech parametrization scheme, and the resulting speech features are computed. Finally, these speech features are evaluated in a common experimental set-up on the speaker verification task. The experimental results, obtained on two well-known speaker recognition databases, show that the Battle-Lemarié wavelet function is the most advantageous one, among all other functions evaluated here, since it leads to the most beneficial speech descriptors. When compared to the baseline Mel-frequency cepstral coefficients (MFCC), a relative reduction of the equal error rate by 4.2 % was observed on the 2001 NIST speaker recognition evaluation database, and by 2.3 % on the Polycost speaker recognition database.en
dc.format.extent10
dc.language.isoeng
dc.relation.ispartofInternational Journal of Speech Technology
dc.titleWavelet basis selection for enhanced speech parametrization in speaker verificationen
dc.contributor.institutionSchool of Engineering and Technology
dc.contributor.institutionCentre for Engineering Research
dc.contributor.institutionInformation Engineering and Processing Architectures
dc.description.statusPeer reviewed
dc.identifier.urlhttp://link.springer.com/article/10.1007%2Fs10772-013-9202-8
dc.relation.schoolSchool of Engineering and Technology
dcterms.dateAccepted2014-03-31
rioxxterms.versionofrecordhttps://doi.org/10.1007/s10772-013-9202-8
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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