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Title: High-Level Speaker Verification via Articulatory-Feature based Sequence Kernels and SVM

Essay Details

Subject: Technology
Author: Ellen B
Date: December 4, 2015
Level: University
Grade: A
Length: 10 / 2848
No of views: 0
Essay rating: good 0, average 0, bad 0 (total score: 0)

Essay text:

Therefore, the method does not fully utilize the discriminative information available in the training data. To fully harness the discriminative information, this paper proposes training a support vector machine (SVM) for computing the verification scores. More precisely, the models of target speakers, individual background speakers, and claimants are converted to AF-supervectors, which form the inputs to an AF-based kernel of the SVM for computing verification scores...

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More precisely, the models of target speakers, individual background speakers, and claimants are converted to AF-supervectors, which form the inputs to an AF-based kernel of the SVM for computing verification scores. Results show that the proposed AF-kernel scoring is complementary to likelihood-ratio scoring, leading to better performance when the two scoring methods are combined...

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