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https://www.researchgate.net/publication/3343440_Support_vector_machines_using_GMM_supervectors_for_speaker_verification
Support vector machines using GMM supervectors for speaker verification Article (PDF Available) in IEEE Signal Processing Letters 13(5):308 - 311 · June 2006 with 688 Reads How we measure 'reads'
http://homepages.inf.ed.ac.uk/srenals/pdf/vinny-thesis.pdf
vector machine(SVM). The support vector machine (SVM) [Vap95] is a discriminative approach that seems well suited to speaker verification. It was developedin the early to mid 1990sand quicklybecamewidely known. Initial speaker verification results using SVMs reported by Schmidt and Gish [SG94] were promising. Its novel
http://www.iitg.ac.in/samudravijaya/publ/09vsrpReportAravind_GLDS.pdf
5 3. Support Vector Machines (SVMs) : SVMs are defined as Linear Learning Machines that can be represented in a dual fashion and operate in a kernel induced feature space[3]. Data not linear in one plane can be mapped to a richer feature space including non linear features where it can be separated using a linear classifier. A simple illustration of this is as below [3]: where yi are the ideal ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.295.3159
BibTeX @ARTICLE{Campbell07speakerverification, author = {William M. Campbell and Joseph P. Campbell and Terry P. Gleason and Douglas A. Reynolds and Senior Member and Wade Shen}, title = {Speaker verification using support vector machines and highlevel features}, journal = {IEEE Trans. Audio, Speech, and Language Process}, year = {2007}, pages = {2085--2094}}
https://www.researchgate.net/publication/224166071_Front-End_Factor_Analysis_for_Speaker_Verification
Front-End Factor Analysis for Speaker Verification. ... This article presents several techniques to combine between Support vector machines (SVM) and Joint Factor Analysis (JFA) model for speaker ...
https://ieeexplore.ieee.org/document/1395965/
Abstract: This paper presents a text-independent speaker verification system using support vector machines (SVMs) with score-space kernels. Score-space kernels generalize Fisher kernels and are based on underlying generative models such as Gaussian mixture models (GMMs).Cited by: 291
https://www.semanticscholar.org/paper/Support-vector-machines-using-GMM-supervectors-for-Campbell-Sturim/8fd5dd993576443ef3dc61be50bd9a6a9cee0cef
Support vector machines using GMM supervectors for speaker verification @article{Campbell2006SupportVM, title={Support vector machines using GMM supervectors for speaker verification}, author={William M. Campbell and Douglas E. Sturim and Douglas A. Reynolds}, journal={IEEE Signal Processing Letters}, year={2006}, volume={13}, pages={308-311} }
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