This HTML5 document contains 46 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
n13http://linked.opendata.cz/ontology/domain/vavai/riv/typAkce/
dctermshttp://purl.org/dc/terms/
n20http://purl.org/net/nknouf/ns/bibtex#
n18http://localhost/temp/predkladatel/
n14http://linked.opendata.cz/resource/domain/vavai/projekt/
n8http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n16http://linked.opendata.cz/ontology/domain/vavai/
n6http://linked.opendata.cz/resource/domain/vavai/zamer/
shttp://schema.org/
skoshttp://www.w3.org/2004/02/skos/core#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n21http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F00216305%3A26230%2F08%3APU76784%21RIV10-MSM-26230___/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n9http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n7http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n15http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n5http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n19http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n17http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n11http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F00216305%3A26230%2F08%3APU76784%21RIV10-MSM-26230___
rdf:type
skos:Concept n16:Vysledek
dcterms:description
This paper describes the acoustic language recognition subsystems of Brno University of Technology (BUT) which contributed to the BUT main submission to the NIST LRE 2007. Two main techniques are employed in the subsystems discriminative training in terms of Maximum Mutual Information, and channel compensation in terms of eigenchannel adaptation in both, model and feature domain. The complementarity of the approaches is analyzed. This paper describes the acoustic language recognition subsystems of Brno University of Technology (BUT) which contributed to the BUT main submission to the NIST LRE 2007. Two main techniques are employed in the subsystems discriminative training in terms of Maximum Mutual Information, and channel compensation in terms of eigenchannel adaptation in both, model and feature domain. The complementarity of the approaches is analyzed.
dcterms:title
Discriminative Training and Channel Compensation for Acoustic Language Recognition Discriminative Training and Channel Compensation for Acoustic Language Recognition
skos:prefLabel
Discriminative Training and Channel Compensation for Acoustic Language Recognition Discriminative Training and Channel Compensation for Acoustic Language Recognition
skos:notation
RIV/00216305:26230/08:PU76784!RIV10-MSM-26230___
n3:aktivita
n5:Z n5:P
n3:aktivity
P(GA102/08/0707), P(GP102/06/P383), Z(MSM0021630528)
n3:dodaniDat
n11:2010
n3:domaciTvurceVysledku
n8:4922514 n8:7822995 Hubeika, Valiantsina n8:9799605
n3:druhVysledku
n17:D
n3:duvernostUdaju
n7:S
n3:entitaPredkladatele
n21:predkladatel
n3:idSjednocenehoVysledku
363778
n3:idVysledku
RIV/00216305:26230/08:PU76784
n3:jazykVysledku
n15:eng
n3:klicovaSlova
language recognition<br>
n3:klicoveSlovo
n9:language%20recognition%3Cbr%3E
n3:kontrolniKodProRIV
[88D69BC47F6A]
n3:mistoKonaniAkce
Brisbane, Australia
n3:mistoVydani
Brisbane
n3:nazevZdroje
Proc. Interspeech 2008
n3:obor
n19:JC
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:projekt
n14:GA102%2F08%2F0707 n14:GP102%2F06%2FP383
n3:rokUplatneniVysledku
n11:2008
n3:tvurceVysledku
Schwarz, Petr Matějka, Pavel Burget, Lukáš Hubeika, Valiantsina
n3:typAkce
n13:WRD
n3:zahajeniAkce
2008-09-22+02:00
n3:zamer
n6:MSM0021630528
s:issn
1990-9772
s:numberOfPages
4
n20:hasPublisher
International Speech Communication Association
n18:organizacniJednotka
26230