Improving the PLDA based speaker verification in limited microphone data conditions

Kanagasundaram, Ahilan, Dean, David, Gonzalez-Dominguez, Javier, Sridharan, Sridha, Ramos, Daniel, & Gonzalez-Rodriguez, Joaquin (2013) Improving the PLDA based speaker verification in limited microphone data conditions. In In Proceedings of the 14th Annual Conference of the International Speech Communication Association, International Speech Communication Association (ISCA ), Lyon, France, pp. 3674-3678.

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A significant amount of speech data is required to develop a robust speaker verification system, but it is difficult to find enough development speech to match all expected conditions. In this paper we introduce a new approach to Gaussian probabilistic linear discriminant analysis (GPLDA) to estimate reliable model parameters as a linearly weighted model taking more input from the large volume of available telephone data and smaller proportional input from limited microphone data. In comparison to a traditional pooled training approach, where the GPLDA model is trained over both telephone and microphone speech, this linear-weighted GPLDA approach is shown to provide better EER and DCF performance in microphone and mixed conditions in both the NIST 2008 and NIST 2010 evaluation corpora. Based upon these results, we believe that linear-weighted GPLDA will provide a better approach than pooled GPLDA, allowing for the further improvement of GPLDA speaker verification in conditions with limited development data.

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5 citations in Scopus
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ID Code: 63027
Item Type: Conference Paper
Refereed: Yes
Keywords: Speaker verification, i-vectors, PLDA
ISSN: 2308-457X
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600)
Divisions: Past > Institutes > Information Security Institute
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright © 2013 ISCA.
Deposited On: 30 Sep 2013 03:24
Last Modified: 21 Jun 2017 14:48

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