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GLEMBEK, O. BURGET, L. KENNY, P. KARAFIÁT, M. MATĚJKA, P.
Originální název
Simplification and optimization of I-Vector Extraction
Typ
článek ve sborníku mimo WoS a Scopus
Jazyk
angličtina
Originální abstrakt
We managed to reduce the memory requirements and processing time for the i-vector extractor training so that higher dimensions can be now used while retaining the recognition accuracy. As for i-vector extraction, we managed to reduce the complexity of the algorithm with sacrificing little recognition accuracy, which makes this technique usable in small-scale devices.
Klíčová slova
speaker recognition, i-vectors, Joint Factor Analysis, PCA, HLDA
Autoři
GLEMBEK, O.; BURGET, L.; KENNY, P.; KARAFIÁT, M.; MATĚJKA, P.
Rok RIV
2011
Vydáno
22. 5. 2011
Nakladatel
IEEE Signal Processing Society
Místo
Praha
ISBN
978-1-4577-0537-3
Kniha
Proceedings of the 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Strany od
4516
Strany do
4519
Strany počet
4
URL
http://www.fit.vutbr.cz/research/groups/speech/publi/2011/glembek_icassp2011_4516.pdf
BibTex
@inproceedings{BUT76376, author="Ondřej {Glembek} and Lukáš {Burget} and Patrick {Kenny} and Martin {Karafiát} and Pavel {Matějka}", title="Simplification and optimization of I-Vector Extraction", booktitle="Proceedings of the 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011", year="2011", pages="4516--4519", publisher="IEEE Signal Processing Society", address="Praha", isbn="978-1-4577-0537-3", url="http://www.fit.vutbr.cz/research/groups/speech/publi/2011/glembek_icassp2011_4516.pdf" }