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- W2121831722 abstract "We present a comparative study of several SVM speaker verification (SV) systems based on sequence kernels: the GMM-supervectors kernel, the fisher kernel, the Generalized linear discriminant sequence (GLDS) kernel, our feature space normalized sequence (FSNS) kernel and a ldquonovelrdquo sequence kernel in SV, the correlation kernel. We also compare these SVM systems to the conventional generative UBM-GMM. We carry out experiments on the NIST'2005 SRE evaluation set. The results show that the FSNS system yields comparable performances to UBM-GMM and significantly outperforms GLDS. They also show that the GMM-supervectors system outperforms all the others. Finally, they show that the best performances are achieved by fusing the FSNS and the GMM-supervectors systems." @default.
- W2121831722 created "2016-06-24" @default.
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- W2121831722 date "2009-04-01" @default.
- W2121831722 modified "2023-09-30" @default.
- W2121831722 title "A comparison between sequence kernels for SVM speaker verification" @default.
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- W2121831722 doi "https://doi.org/10.1109/icassp.2009.4960565" @default.
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