About: Fast Estimation of Gaussian Mixture Model Parameters on GPU using CUDA

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Gaussian Mixture Model (GMM) statistics are required for maximum likelihood training as well as for adaptation techniques. In order to train/adapt a reliable model a lot of data are needed, what makes the estimation process time consuming. The paper presents an efficient implementation of estimation of GMM statistics on GPU using NVIDIA's Compute Unified Device Architecture (CUDA). Also an augmentation of the standard CPU version is proposed utilizing SSE instructions. Time consumptions of presented methods are tested on a large dataset of real speech data from the NIST Speaker Recognition Evaluation 2008. Estimation on GPU proves to be 100 times faster than the standard CPU version and 30 times faster than the SSE version assuming more than 256 mixtures, thus a huge speed-up was achieved without any approximations made in the estimation formulas. Proposed implementation was also compared to other implementations developed by other departments over the world and proved to be the fastest. Gaussian Mixture Model (GMM) statistics are required for maximum likelihood training as well as for adaptation techniques. In order to train/adapt a reliable model a lot of data are needed, what makes the estimation process time consuming. The paper presents an efficient implementation of estimation of GMM statistics on GPU using NVIDIA's Compute Unified Device Architecture (CUDA). Also an augmentation of the standard CPU version is proposed utilizing SSE instructions. Time consumptions of presented methods are tested on a large dataset of real speech data from the NIST Speaker Recognition Evaluation 2008. Estimation on GPU proves to be 100 times faster than the standard CPU version and 30 times faster than the SSE version assuming more than 256 mixtures, thus a huge speed-up was achieved without any approximations made in the estimation formulas. Proposed implementation was also compared to other implementations developed by other departments over the world and proved to be the fastest. (en)
Title	Fast Estimation of Gaussian Mixture Model Parameters on GPU using CUDA Fast Estimation of Gaussian Mixture Model Parameters on GPU using CUDA (en)
skos:prefLabel	Fast Estimation of Gaussian Mixture Model Parameters on GPU using CUDA Fast Estimation of Gaussian Mixture Model Parameters on GPU using CUDA (en)
skos:notation	RIV/49777513:23520/11:43898222!RIV12-GA0-23520___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GA102/08/0707), P(LC536)
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Vaněk, Jan Zajíc, Zbyněk Machlica, Lukáš
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Západočeská univerzita v Plzni / Fakulta aplikovaných věd
http://linked.open...dnocenehoVysledku	199359
http://linked.open...ai/riv/idVysledku	RIV/49777513:23520/11:43898222
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	CUDA, SSE, GMM, robust, GMM, EM, parallel implementation (en)
http://linked.open.../riv/klicoveSlovo	robust EM GMM SSE parallel implementation CUDA
http://linked.open...ontrolniKodProRIV	[FB278945F486]
http://linked.open...v/mistoKonaniAkce	Gwangju, Jižní Korea
http://linked.open...i/riv/mistoVydani	Los Alamitos, California, USA
http://linked.open...i/riv/nazevZdroje	The 12th International Conference on Parallel and Distributed Computing, Applications and Technologies
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Speech Recognition under Real-World Conditions Integrated center for natural language processing
http://linked.open...UplatneniVysledku	2011
http://linked.open...iv/tvurceVysledku	Vaněk, Jan Machlica, Lukáš Zajíc, Zbyněk
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2011-10-20 (xsd:date)
number of pages	6 (xsd:int)
http://bibframe.org/vocab/doi	10.1109/PDCAT.2011.40
http://purl.org/ne...btex#hasPublisher	IEEE Computer Society Conference Publishing Services (CPS)
https://schema.org/isbn	978-0-7695-4564-6
http://localhost/t...ganizacniJednotka	23520

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