i-vector based speaker recognition on short utterances
Kanagasundaram, Ahilan, Vogt, Robbie, Dean, David B., Sridharan, Sridha, & Mason, Michael W. (2011) i-vector based speaker recognition on short utterances. In Proceedings of the 12th Annual Conference of the International Speech Communication Association, International Speech Communication Association (ISCA ), Firenze Fiera, Florence, pp. 2341-2344.
Robust speaker verification on short utterances remains a key consideration when deploying automatic speaker recognition, as many real world applications often have access to only limited duration speech data. This paper explores how the recent technologies focused around total variability modeling behave when training and testing utterance lengths are reduced. Results are presented which provide a comparison of Joint Factor Analysis (JFA) and i-vector based systems including various compensation techniques; Within-Class Covariance Normalization (WCCN), LDA, Scatter Difference Nuisance Attribute Projection (SDNAP) and Gaussian Probabilistic Linear Discriminant Analysis (GPLDA). Speaker verification performance for utterances with as little as 2 sec of data taken from the NIST Speaker Recognition Evaluations are presented to provide a clearer picture of the current performance characteristics of these techniques in short utterance conditions.
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|Item Type:||Conference Paper|
|Keywords:||speaker verification, i-vector, short utterance, Gaussian PLDA|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Institutes > Information Security Institute
Past > Schools > School of Engineering Systems
|Copyright Owner:||Copyright 2011 ISCA|
|Deposited On:||04 Oct 2011 22:27|
|Last Modified:||02 Jun 2015 04:53|
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