Detail publikačního výsledku

Feature Gaussianization for Speech Recognition

MATĚJKA, P., ČERNOCKÝ, J.

Originální název

Feature Gaussianization for Speech Recognition

Anglický název

Feature Gaussianization for Speech Recognition

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

In Hidden Markov models, speech data are modeled by Gaussian distributions. In this paper, we propose to Gaussianize the features to better fit to this modeling. A distribution of the data is estimated and a transform function is derived. We test three methods of the transform estimation (global, speaker based, frame based) and report results on the SPINE 2000 task with Sphinx recognizer. We conclude that the proposed method is a cheap way to increase the recognition accuracy.

Anglický abstrakt

In Hidden Markov models, speech data are modeled by Gaussian distributions. In this paper, we propose to Gaussianize the features to better fit to this modeling. A distribution of the data is estimated and a transform function is derived. We test three methods of the transform estimation (global, speaker based, frame based) and report results on the SPINE 2000 task with Sphinx recognizer. We conclude that the proposed method is a cheap way to increase the recognition accuracy.

Klíčová slova v angličtině

speaker speach recognition gaussianization HMM

Autoři

MATĚJKA, P., ČERNOCKÝ, J.

Vydáno

14.05.2002

Nakladatel

Slovak University of Technology in Bratislava

Místo

Bratislava,Slovak Republic

ISBN

80-227-1700-2

Kniha

Conference Proceedings

Strany od

93

Strany počet

4

BibTex

@inproceedings{BUT5411,
  author="Pavel {Matějka} and Jan {Černocký}",
  title="Feature Gaussianization for Speech Recognition",
  booktitle="Conference Proceedings",
  year="2002",
  pages="4",
  publisher="Slovak University of Technology in Bratislava",
  address="Bratislava,Slovak Republic",
  isbn="80-227-1700-2"
}