Improved speaker verification through probabilistic subspace adaptation
Conference Paper, Proceedings of 8th European Conference on Speech Communication and Technology (EUROSPEECH '03), pp. 2021 - 2024, September, 2003
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 text independent speaker verification.
BibTeX
@conference{Lucey-2003-121087,author = {S. Lucey and T. Chen},
title = {Improved speaker verification through probabilistic subspace adaptation},
booktitle = {Proceedings of 8th European Conference on Speech Communication and Technology (EUROSPEECH '03)},
year = {2003},
month = {September},
pages = {2021 - 2024},
}
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