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"
}