MLLR Transforms Based Speaker Recognition in Broadcast Streams

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F09%3A%230001399" target="_blank" >RIV/46747885:24220/09:#0001399 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
MLLR Transforms Based Speaker Recognition in Broadcast Streams
Original language description
This paper deals with utilization of maximum likelihood linear regression (MLLR) adaptation transforms for speaker recognition in broadcast news streams. This task is specific particularly for widely varying acoustic conditions, microphones, transmissionchannels, background noise and short duration of recordings (usually in the range from 5 to 15 seconds). MLLR transforms based features are modeled using support vector machines (SVM). Obtained results are compared with a GMM based system with traditional MFCC features. The paper also deals with inter-session variability compensation techniques suitable for both systems and emphases the importance of feature vector scaling for SVM based system.
Czech name
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Czech description
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Project
<a href="/en/project/VD20072010B16" target="_blank" >VD20072010B16: Overcoming language barrier that complicates investigation of terrorism financing and relevant financial criminality</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Lecture Notes in Artificial Inteligence, LNAI 5641
ISBN
978-3-642-03319-3
ISSN
0302-9743
e-ISSN
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Number of pages
9
Pages from-to
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Publisher name
SPRINGER-VERLAG BERLIN
Place of publication
BERLIN, GERMANY
Event location
Prague, CZECH REPUBLIC
Event date
Jan 1, 2008
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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