Detail publikace

Adaptation of Multilingual Stacked Bottle-neck Neural Network Structure for New Language

GRÉZL, F. KARAFIÁT, M. VESELÝ, K.

Originální název

Adaptation of Multilingual Stacked Bottle-neck Neural Network Structure for New Language

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

In this paper a multilingual training of Stacked Bottle- Neck neural network structure for feature extraction is addressed. While for languages with plentiful resources, the optimal approach is to train the BN-NN on the target data, limited resources call for re-using data from other languages.

Klíčová slova

feature extraction, Bottle-neck features, neural network adaptation, multilingual neural networks, Stacked Bottle- Neck structure

Autoři

GRÉZL, F.; KARAFIÁT, M.; VESELÝ, K.

Rok RIV

2014

Vydáno

4. 5. 2014

Nakladatel

IEEE Signal Processing Society

Místo

Florencie

ISBN

978-1-4799-2892-7

Kniha

Proceedings of ICASSP 2014

Strany od

7704

Strany do

7708

Strany počet

5

URL

http://www.fit.vutbr.cz/research/groups/speech/publi/2014/grezl_icassp2014_p7704_adapation.pdf

BibTex

@inproceedings{BUT111544,
  author="František {Grézl} and Martin {Karafiát} and Karel {Veselý}",
  title="Adaptation of Multilingual Stacked Bottle-neck Neural Network Structure for New Language",
  booktitle="Proceedings of ICASSP 2014",
  year="2014",
  pages="7704--7708",
  publisher="IEEE Signal Processing Society",
  address="Florencie",
  doi="10.1109/ICASSP.2014.6855089",
  isbn="978-1-4799-2892-7",
  url="http://www.fit.vutbr.cz/research/groups/speech/publi/2014/grezl_icassp2014_p7704_adapation.pdf"
}