Publication detail

Simplification and optimization of I-Vector Extraction

GLEMBEK, O. BURGET, L. KENNY, P. KARAFIÁT, M. MATĚJKA, P.

Original Title

Simplification and optimization of I-Vector Extraction

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

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.

Keywords

speaker recognition, i-vectors, Joint Factor Analysis, PCA, HLDA

Authors

GLEMBEK, O.; BURGET, L.; KENNY, P.; KARAFIÁT, M.; MATĚJKA, P.

RIV year

2011

Released

22. 5. 2011

Publisher

IEEE Signal Processing Society

Location

Praha

ISBN

978-1-4577-0537-3

Book

Proceedings of the 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011

Pages from

4516

Pages to

4519

Pages count

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"
}