About: Initialization of fMLLR with Sufficient Statistics from Similar Speakers

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	One of the most utilized adaptation techniques is the feature Maximum Likelihood Linear Regression (fMLLR). In comparison with other adaptation methods the number of free parameters to be estimated significantly decreases. Thus, the method is well suited for situations with small amount of adaptation data. However, fMLLR still fails in situations with extremely small data sets. Such situations can be solved through proper initialization of fMLLR estimation adding some a-priori information. In this paper a novel approach is proposed solving the problem of fMLLR initialization involving statistics from speakers acoustically close to the speaker to be adapted. Proposed initialization suitably substitutes missing adaptation data with similar data from a training database, fMLLR estimation becomes well-conditioned, and the accuracy of the recognition system increases even in situations with extremely small data sets. One of the most utilized adaptation techniques is the feature Maximum Likelihood Linear Regression (fMLLR). In comparison with other adaptation methods the number of free parameters to be estimated significantly decreases. Thus, the method is well suited for situations with small amount of adaptation data. However, fMLLR still fails in situations with extremely small data sets. Such situations can be solved through proper initialization of fMLLR estimation adding some a-priori information. In this paper a novel approach is proposed solving the problem of fMLLR initialization involving statistics from speakers acoustically close to the speaker to be adapted. Proposed initialization suitably substitutes missing adaptation data with similar data from a training database, fMLLR estimation becomes well-conditioned, and the accuracy of the recognition system increases even in situations with extremely small data sets. (en)
Title	Initialization of fMLLR with Sufficient Statistics from Similar Speakers Initialization of fMLLR with Sufficient Statistics from Similar Speakers (en)
skos:prefLabel	Initialization of fMLLR with Sufficient Statistics from Similar Speakers Initialization of fMLLR with Sufficient Statistics from Similar Speakers (en)
skos:notation	RIV/49777513:23520/11:43898196!RIV12-GA0-23520___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(GA102/08/0707), P(LC536), S
http://linked.open...iv/cisloPeriodika	6836
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Zajíc, Zbyněk Müller, Luděk Machlica, Lukáš
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	Západočeská univerzita v Plzni / Fakulta aplikovaných věd
http://linked.open...dnocenehoVysledku	204873
http://linked.open...ai/riv/idVysledku	RIV/49777513:23520/11:43898196
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	fMLLR, adaptation, sufficient statistics, speech recognition, robustness,initialization. (en)
http://linked.open.../riv/klicoveSlovo	fMLLR initialization. sufficient statistics adaptation robustness speech recognition
http://linked.open...odStatuVydavatele	DE - Spolková republika Německo
http://linked.open...ontrolniKodProRIV	[1CEB7BC95AF0]
http://linked.open...i/riv/nazevZdroje	Lecture Notes in Computer Science
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...v/svazekPeriodika	Neuveden
http://linked.open...iv/tvurceVysledku	Machlica, Lukáš Zajíc, Zbyněk Müller, Luděk
issn	0302-9743
number of pages	8 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-3-642-23538-2_24
http://localhost/t...ganizacniJednotka	23520

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