Publication detail

Study of Probabilistic and Bottle-Neck Features in Multilingual Environment

GRÉZL, F. KARAFIÁT, M. JANDA, M.

Original Title

Study of Probabilistic and Bottle-Neck Features in Multilingual Environment

English Title

Study of Probabilistic and Bottle-Neck Features in Multilingual Environment

Type

conference paper

Language

en

Original Abstract

The article studies properties of features obtained using neural networks in milti=lingual recognition systems. The neural networks are trained on particular data and thus it is interesting to observe bahavior of these features when used on data from different language.

English abstract

The article studies properties of features obtained using neural networks in milti=lingual recognition systems. The neural networks are trained on particular data and thus it is interesting to observe bahavior of these features when used on data from different language.

Keywords

Neural networks, multilingual apeech recognition, Botle-Neck features, probabilistic features

RIV year

2011

Released

11.12.2011

Publisher

IEEE Signal Processing Society

Location

Hilton Waikoloa Village, Big Island, Hawaii

ISBN

978-1-4673-0366-8

Book

Proceedings of ASRU 2011

Edition

NEUVEDEN

Edition number

NEUVEDEN

Pages from

359

Pages to

364

Pages count

6

URL

Documents

BibTex


@inproceedings{BUT76454,
  author="František {Grézl} and Martin {Karafiát} and Miloš {Janda}",
  title="Study of Probabilistic and Bottle-Neck Features in Multilingual Environment",
  annote="The article studies properties of features obtained using neural networks in
milti=lingual recognition systems. The neural networks are trained on particular
data and thus it is interesting to observe bahavior of these features when used
on data from different language.",
  address="IEEE Signal Processing Society",
  booktitle="Proceedings of ASRU 2011",
  chapter="76454",
  edition="NEUVEDEN",
  howpublished="print",
  institution="IEEE Signal Processing Society",
  year="2011",
  month="december",
  pages="359--364",
  publisher="IEEE Signal Processing Society",
  type="conference paper"
}