Detail publikace

Combination of Speech Features Using Smoothed Heteroscedastic Linear Discriminant Analysis

BURGET, L.

Originální název

Combination of Speech Features Using Smoothed Heteroscedastic Linear Discriminant Analysis

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Feature combination techniques based on PCA, LDA and HLDA are compared in experiments where limited amount of training data is available. Success with feature combination can be quite dependent on proper estimation of statistics required by the used technique. Insufficiency of training data is, therefore, an important problem, which has to be taken in to account in our experiments.
Besides of some standard approaches increasing robustness of statistic estimation, methods based on combination of LDA and HLDA are proposed. An improved recognition performance obtained using these methods is demonstrated in experiments.

Klíčová slova

speech recognition, LDA, HLDA, feature extraction, feature combination

Autoři

BURGET, L.

Rok RIV

2004

Vydáno

7. 6. 2004

Nakladatel

Sunjin Printing Co,

Místo

Jeju island

Strany od

2549

Strany do

2552

Strany počet

4

URL

http://www.fit.vutbr.cz/~burget/publications/burget_icslp2004.pdf

BibTex

@inproceedings{BUT17132,
  author="Lukáš {Burget}",
  title="Combination of Speech Features Using Smoothed Heteroscedastic Linear Discriminant Analysis",
  booktitle="Proc. 8th International Conference on Spoken Language Processing",
  year="2004",
  pages="2549--2552",
  publisher="Sunjin Printing Co,",
  address="Jeju island",
  url="http://www.fit.vutbr.cz/~burget/publications/burget_icslp2004.pdf"
}