Detail publikace

Neural network topologies and bottle neck features in speech recognition

GRÉZL, F. KARAFIÁT, M. ČERNOCKÝ, J.

Originální název

Neural network topologies and bottle neck features in speech recognition

Typ

prezentace, poster

Jazyk

angličtina

Originální abstrakt

Different neural net topologies for estimating features for speechrecognition were presented. We introduced bottle-neck structure intopreviously proposed Split Context. This was done mainly to reduce sizeof resulting neural net, which serves as feature estimator. Whenbottle-neck outputs are used also as final outputs from neural networkinstead of probability estimates, the reduction of word error rate isalso reached.

Klíčová slova

neural networks, topologies, speech recognition, bottle-neck features

Autoři

GRÉZL, F.; KARAFIÁT, M.; ČERNOCKÝ, J.

Vydáno

28. 6. 2007

Místo

Brno

Strany od

78

Strany do

82

Strany počet

5

URL

http://www.fit.vutbr.cz/~grezl/publi/mlmi2007.pdf

BibTex

@misc{BUT63689,
  author="František {Grézl} and Martin {Karafiát} and Jan {Černocký}",
  title="Neural network topologies and bottle neck features in speech recognition",
  year="2007",
  pages="78--82",
  address="Brno",
  url="http://www.fit.vutbr.cz/~grezl/publi/mlmi2007.pdf",
  note="presentation, poster"
}