An Efficient Implementation of Probabilistic Linear Discriminant Analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F13%3A43919389" target="_blank" >RIV/49777513:23520/13:43919389 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6639157" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6639157</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICASSP.2013.6639157" target="_blank" >10.1109/ICASSP.2013.6639157</a>
Alternative languages
Result language
angličtina
Original language name
An Efficient Implementation of Probabilistic Linear Discriminant Analysis
Original language description
Probabilistic Linear Discriminant Analysis (PLDA), used particularly in image and speech processing for face and speaker recognition, respectively, is a generative model requesting lots of data to be trained. In the paper several enhancements concerningthe implementation of the estimation algorithm of PLDA are proposed providing substantial computational savings. At first, an inverse of a huge matrix is replaced by an inversion of two significantly smaller matrices. Subsequently, it is shown how to avoid the need to process the whole data set in each iteration of the estimation algorithm. Supplementary results are presented on NIST SRE 2008.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
ISBN
978-1-4799-0356-6
ISSN
1520-6149
e-ISSN
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Number of pages
5
Pages from-to
7678-7682
Publisher name
IEEE
Place of publication
New York
Event location
Vancouver, BC, Canada
Event date
May 26, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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