Publication result detail

Using Smoothed Heteroscedastic Linear Discriminant Analysis in Large Vocabulary Continuous Speech Recognition System

KARAFIÁT, M.; BURGET, L.; ČERNOCKÝ, J.

Original Title

Using Smoothed Heteroscedastic Linear Discriminant Analysis in Large Vocabulary Continuous Speech Recognition System

English Title

Using Smoothed Heteroscedastic Linear Discriminant Analysis in Large Vocabulary Continuous Speech Recognition System

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

In this work, we verify that SHLDA can be advantageously used also for Large Vocabulary
Continuous Speech Recognition.

English abstract

In this work, we verify that SHLDA can be advantageously used also for Large Vocabulary
Continuous Speech Recognition.

Keywords

speech recognition, LVCSR, HLDA, feature transform, dimensionality reduction

Key words in English

speech recognition, LVCSR, HLDA, feature transform, dimensionality reduction

Authors

KARAFIÁT, M.; BURGET, L.; ČERNOCKÝ, J.

Released

13.07.2005

Publisher

University of Edinburgh

Location

Edinbourgh, Scotland

Book

2nd Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms

Edition

tento článek nebyl zařazen mezi Revised Selected Papers, nevyšel v LNCS 3869

Pages from

1

Pages to

8

Pages count

8

URL

https://www.fit.vutbr.cz/~karafiat/publi/2005/karafiat_mlmi2005.pdf

BibTex

@inproceedings{BUT18264,
  author="Martin {Karafiát} and Lukáš {Burget} and Jan {Černocký}",
  title="Using Smoothed Heteroscedastic Linear Discriminant Analysis in Large Vocabulary Continuous Speech Recognition System",
  booktitle="2nd Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms",
  year="2005",
  series="tento článek nebyl zařazen mezi Revised Selected Papers, nevyšel v LNCS 3869",
  pages="1--8",
  publisher="University of Edinburgh",
  address="Edinbourgh, Scotland",
  url="https://www.fit.vutbr.cz/~karafiat/publi/2005/karafiat_mlmi2005.pdf"
}