Short utterance variance modelling and utterance partitioning for PLDA speaker verification

Kanagasundaram, Ahilan, Dean, David, Sridharan, Sridha, Fookes, Clinton B., & Himawan, Ivan (2016) Short utterance variance modelling and utterance partitioning for PLDA speaker verification. In 16th Annual Conference of the International Speech Communication Association (InterSpeech 2016), 8-12 September 2016, San Francisco, CA.


This paper analyses the short utterance probabilistic linear discriminant analysis (PLDA) speaker verification with utterance partitioning and short utterance variance (SUV) modelling approaches. Experimental studies have found that instead of using single long-utterance as enrolment data, if long enrolled utterance is partitioned into multiple short utterances and average of short utterance i-vectors is used as enrolled data, that improves the Gaussian PLDA (GPLDA) speaker verification. This is because short utterance i-vectors have speaker, session and utterance variations, and utterance-partitioning approach compensates the utterance variation. Subsequently, SUV-PLDA is also studied with utterance partitioning approach, and utterance partitioning-based SUV-GPLDA system shows relative improvement of 9% and 16% in EER for NIST 2008 and NIST 2010 truncated 10sec-10sec evaluation condition as utterance partitioning approach compensates the utterance variation and SUV modelling approach compensates the mismatch between full-length development data and short-length evaluation data.

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ID Code: 96308
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: speaker verification, i-vectors, PLDA, SUV, utterance partitioning
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Signal Processing (090609)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Institutes > Information Security Institute
Copyright Owner: Copyright 2016 [Please consult the author]
Deposited On: 22 Jun 2016 23:26
Last Modified: 11 Sep 2016 18:43

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