Tree-based Gaussian mixture models for speaker verification

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005. === The Gaussian mixture model (GMM) performs very effectively in applications such as speech and speaker recognition. However, evaluation speed is greatly reduced when the GMM has a large number of mixture...

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Main Author:	Cilliers, Francois Dirk
Other Authors:	Du Preez, J. A.
Format:	Others
Language:	en
Published:	Stellenbosch : University of Stellenbosch 2006
Subjects:	Dissertations > Electronic engineering Theses > Electronic engineering Automatic speech recognition Speech processing systems Electrical and Electronic Engineering
Online Access:	http://hdl.handle.net/10019.1/1639

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spelling	ndltd-netd.ac.za-oai-union.ndltd.org-sun-oai-scholar.sun.ac.za-10019.1-16392016-01-29T04:02:58Z Tree-based Gaussian mixture models for speaker verification Cilliers, Francois Dirk Du Preez, J. A. University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Dissertations -- Electronic engineering Theses -- Electronic engineering Automatic speech recognition Speech processing systems Electrical and Electronic Engineering Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005. The Gaussian mixture model (GMM) performs very effectively in applications such as speech and speaker recognition. However, evaluation speed is greatly reduced when the GMM has a large number of mixture components. Various techniques improve the evaluation speed by reducing the number of required Gaussian evaluations. 2006-11-01T08:25:54Z 2010-06-01T08:29:18Z 2006-11-01T08:25:54Z 2010-06-01T08:29:18Z 2005-12 Thesis http://hdl.handle.net/10019.1/1639 en University of Stellenbosch 1024437 bytes application/pdf Stellenbosch : University of Stellenbosch
collection	NDLTD
language	en
format	Others
sources	NDLTD
topic	Dissertations -- Electronic engineering Theses -- Electronic engineering Automatic speech recognition Speech processing systems Electrical and Electronic Engineering
spellingShingle	Dissertations -- Electronic engineering Theses -- Electronic engineering Automatic speech recognition Speech processing systems Electrical and Electronic Engineering Cilliers, Francois Dirk Tree-based Gaussian mixture models for speaker verification
description	Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005. === The Gaussian mixture model (GMM) performs very effectively in applications such as speech and speaker recognition. However, evaluation speed is greatly reduced when the GMM has a large number of mixture components. Various techniques improve the evaluation speed by reducing the number of required Gaussian evaluations.
author2	Du Preez, J. A.
author_facet	Du Preez, J. A. Cilliers, Francois Dirk
author	Cilliers, Francois Dirk
author_sort	Cilliers, Francois Dirk
title	Tree-based Gaussian mixture models for speaker verification
title_short	Tree-based Gaussian mixture models for speaker verification
title_full	Tree-based Gaussian mixture models for speaker verification
title_fullStr	Tree-based Gaussian mixture models for speaker verification
title_full_unstemmed	Tree-based Gaussian mixture models for speaker verification
title_sort	tree-based gaussian mixture models for speaker verification
publisher	Stellenbosch : University of Stellenbosch
publishDate	2006
url	http://hdl.handle.net/10019.1/1639
work_keys_str_mv	AT cilliersfrancoisdirk treebasedgaussianmixturemodelsforspeakerverification
_version_	1718163795402031104

Tree-based Gaussian mixture models for speaker verification

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