Detail publikace

Using Gradient Descent Optimization for Acoustics Training from Heterogeneous Data

KARAFIÁT, M. SZŐKE, I. ČERNOCKÝ, J.

Originální název

Using Gradient Descent Optimization for Acoustics Training from Heterogeneous Data

Anglický název

Using Gradient Descent Optimization for Acoustics Training from Heterogeneous Data

Jazyk

en

Originální abstrakt

This paper is on using the gradient descent optimization for acoustics training from heterogeneous data. We study the use of heterogeneous data for training of acoustic models.

Anglický abstrakt

This paper is on using the gradient descent optimization for acoustics training from heterogeneous data. We study the use of heterogeneous data for training of acoustic models.

Dokumenty

BibTex 


@inproceedings{BUT34926,
  author="Martin {Karafiát} and Igor {Szőke} and Jan {Černocký}",
  title="Using Gradient Descent Optimization for Acoustics Training from Heterogeneous Data",
  annote="This paper is on using the gradient descent optimization for acoustics training
from heterogeneous data. We study the use of heterogeneous data for training of
acoustic models.",
  address="Springer Verlag",
  booktitle="Proc. Text, Speech and Dialog 2010",
  chapter="34926",
  edition="LNAI 6231",
  howpublished="print",
  institution="Springer Verlag",
  journal="Lecture Notes in Computer Science (IF 0,513)",
  number="9",
  year="2010",
  month="september",
  pages="322--329",
  publisher="Springer Verlag",
  type="conference paper"
}