Please use this identifier to cite or link to this item: http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/1855
Title: PLDA based Speaker Verification with Weighted LDA Techniques
Authors: Ahilan, K.
Dean, D.
Sridharan, S.
Vogt, R.
Issue Date: 2012
Citation: Kanagasundaram, A., Dean, D., Sridharan, S., & Vogt, R. (2012). PLDA based speaker verification with weighted LDA techniques. In Proceedings of The Speaker and Language Recognition Workshop: Odyssey 2012 (pp. 34-38). International Speech Communication Association.
Abstract: This paper investigates the use of the dimensionality-reduction techniques weighted linear discriminant analysis (WLDA), and weighted median fisher discriminant analysis (WMFD), before probabilistic linear discriminant analysis (PLDA) modeling for the purpose of improving speaker verification performance in the presence of high inter-session variability. Recently it was shown that WLDA techniques can provide improvement over traditional linear discriminant analysis (LDA) for channel compensation in i-vector based speaker verification systems. We show in this paper that the speaker discriminative information that is available in the distance between pair of speakers clustered in the development i-vector space can also be exploited in heavy-tailed PLDA modeling by using the weighted discriminant approaches prior to PLDA modeling. Based upon the results presented within this paper using the NIST 2008 Speaker Recognition Evaluation dataset, we believe that WLDA and WMFD projections before PLDA modeling can provide an improved approach when compared to uncompensated PLDA modeling for i-vector based speaker verification systems
URI: http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/1855
Appears in Collections:Electrical & Electronic Engineering

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