Improved speaker verification through probabilistic subspace adaptation
Lucey S. Chen T.
Lucey S.
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Abstract
In this paper we propose a new adaptation technique for improved text-independent speaker verification with limited amounts of training data using Gaussian mixture models (GMMs). The technique, referred to as probabilistic subspace adaptation (PSA), employs a probabilistic subspace description of how a client?s parametric representation (i.e. GMM) is allowed to vary. Our technique is compared to traditional maximum a posteriori (MAP) adaptation, or relevance adaptation (RA), and maximum likelihood eigen-decomposition (MLED), or subspace adaptation (SA) techniques. Results are given on a subset of the XM2VTS databases for the task of textindependent speaker verification.
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EUROSPEECH 2003 - 8th European Conference on Speech Communication and Technology
Publisher
International Speech Communication Association
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Date
2003
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Conference Paper