Detail výsledku
Language Recognition in iVectors Space
Plchot Oldřich, Ing., Ph.D., UPGM (FIT)
Burget Lukáš, doc. Ing., Ph.D., UPGM (FIT)
Glembek Ondřej, Ing., Ph.D., UPGM (FIT)
Matějka Pavel, Ing., Ph.D., UPGM (FIT)
We have introduced a novel approach for language recognition.Three classifiers (linear generative model, SVM and logistic regression)have been tested in the iVector space, and all outperformthe state-of-the-art JFA system. Very simple and fast classifierbased on linear generative model provides excellent performanceover all conditions. The advantage of this classifieris also its scalability: addition of a new language only requiresestimating the mean over the corresponding iVectors. Most ofthe computational load is in the iVector generation. Hence, as anext step, we will try to obtain iVectors from the utterances andthe corresponding sufficient statistics in a more direct way.
Acoustic Language Recognition, iVectors, JointFactor Analysis
@inproceedings{BUT76437,
author="David {Martínez González} and Oldřich {Plchot} and Lukáš {Burget} and Ondřej {Glembek} and Pavel {Matějka}",
title="Language Recognition in iVectors Space",
booktitle="Proceedings of Interspeech 2011",
year="2011",
journal="Proceedings of Interspeech",
volume="2011",
number="8",
pages="861--864",
publisher="International Speech Communication Association",
address="Florence",
isbn="978-1-61839-270-1",
issn="1990-9772",
url="http://www.fit.vutbr.cz/research/groups/speech/publi/2011/martinez_interspeech2011_291.pdf"
}
Výzkum informačních technologií z hlediska bezpečnosti, MŠMT, Institucionální prostředky SR ČR (např. VZ, VC), MSM0021630528, zahájení: 2007-01-01, ukončení: 2013-12-31, řešení