Publication detail

Parallel training of neural networks for speech recognition

KONTÁR, S.

Original Title

Parallel training of neural networks for speech recognition

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

In speech recognition, forward multi-layer neural networks are used as classifiers for phoneme recognizers, for speech parameterization, in language models, and for language or speaker recognition. This paper discusses possibilities of training forward multi-layer neural networks using parallel algorithms. The need for parallel training of neural networks is caused by huge quantity of training data used in speech recognition. Synchronous and asynchronous variants of the training are discussed and experimental results are reported on a real speech processing task.

Keywords

Artificial neural networks, speech recognition, parallel training algorithms

Authors

KONTÁR, S.

RIV year

2006

Released

26. 9. 2006

Publisher

Brno University of Technology

Location

Brno

ISBN

80-214-3195-4

Book

Proc. 12th International Conference on Soft Computing MENDEL'06

Pages from

6037

Pages to

6042

Pages count

6

URL

http://www.fit.vutbr.cz/~cernocky/publi/2006/mendel_2006.pdf

BibTex

@inproceedings{BUT22372,
  author="Stanislav {Kontár}",
  title="Parallel training of neural networks for speech recognition",
  booktitle="Proc. 12th International Conference on Soft Computing MENDEL'06",
  year="2006",
  pages="6037--6042",
  publisher="Brno University of Technology",
  address="Brno",
  isbn="80-214-3195-4",
  url="http://www.fit.vutbr.cz/~cernocky/publi/2006/mendel_2006.pdf"
}