About: Comparison of Generative and Discriminative Approaches for Speaker Recognition with Limited Data

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	This paper presents a comparison of three different speaker recognition methods deployed in a broadcast news processing system. We focus on how the generative and discriminative nature of these methods affects the speaker recognition framework and we also deal with intersession variability compensation techniques in more detail, which are of great interest in broadcast processing domain. Performed experiments are specific particularly for the very limited amount of data used for both speaker enrollment (typically ranging from 30 to 60 seconds) and recognition (typically ranging from 5 to 15 seconds). Our results show that the system based on Gaussian Mixture Models (GMMs) outperforms both systems based on Support Vector Machines (SVMs) but its drawback is higher computational cost. This paper presents a comparison of three different speaker recognition methods deployed in a broadcast news processing system. We focus on how the generative and discriminative nature of these methods affects the speaker recognition framework and we also deal with intersession variability compensation techniques in more detail, which are of great interest in broadcast processing domain. Performed experiments are specific particularly for the very limited amount of data used for both speaker enrollment (typically ranging from 30 to 60 seconds) and recognition (typically ranging from 5 to 15 seconds). Our results show that the system based on Gaussian Mixture Models (GMMs) outperforms both systems based on Support Vector Machines (SVMs) but its drawback is higher computational cost. (en)
Title	Comparison of Generative and Discriminative Approaches for Speaker Recognition with Limited Data Comparison of Generative and Discriminative Approaches for Speaker Recognition with Limited Data (en)
skos:prefLabel	Comparison of Generative and Discriminative Approaches for Speaker Recognition with Limited Data Comparison of Generative and Discriminative Approaches for Speaker Recognition with Limited Data (en)
skos:notation	RIV/46747885:24220/09:#0001353!RIV10-GA0-24220___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GA102/08/0707), P(GP102/07/P430)
http://linked.open...iv/cisloPeriodika	3
http://linked.open...vai/riv/dodaniDat	2010
http://linked.open...aciTvurceVysledku	Žďánský, Jindřich Červa, Petr Silovský, Jan
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Technická univerzita v Liberci / Fakulta mechatroniky, informatiky a mezioborových studií
http://linked.open...dnocenehoVysledku	307716
http://linked.open...ai/riv/idVysledku	RIV/46747885:24220/09:#0001353
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Speaker recognition; Gaussian Mixture Models (GMM); Support Vector Machines (SVM) (en)
http://linked.open.../riv/klicoveSlovo	Speaker recognition Support Vector Machines (SVM) Gaussian Mixture Models (GMM)
http://linked.open...odStatuVydavatele	CZ - Česká republika
http://linked.open...ontrolniKodProRIV	[518646BB7E11]
http://linked.open...i/riv/nazevZdroje	RADIOENGINEERING
http://linked.open...in/vavai/riv/obor	JC
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 Automatic audio signal segmentation for spoken document retrieval tasks
http://linked.open...UplatneniVysledku	2009
http://linked.open...v/svazekPeriodika	18
http://linked.open...iv/tvurceVysledku	Silovský, Jan Červa, Petr Žďánský, Jindřich
issn	1210-2512
number of pages	10 (xsd:int)
http://localhost/t...ganizacniJednotka	24220

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