Publication Details

Region Dependent Linear Transforms in Multilingual Speech Recognition

KARAFIÁT, M.; JANDA, M.; ČERNOCKÝ, J.; BURGET, L. Region Dependent Linear Transforms in Multilingual Speech Recognition. In Proc. International Conference on Acoustics, Speech, and Signal Processing 2012. Kyoto: IEEE Signal Processing Society, 2012. p. 4885-4888. ISBN: 978-1-4673-0044-5.
Czech title
Lineární transformace závislé na regionech v multilingválním rozpoznávání řeči
Type
conference paper
Language
English
Authors
URL
Keywords

HLDA, Region Dependent Transforms, Minimum Phone Error, fMPE, multilingual speech recognition

Abstract

In today's speech recognition systems, linear or nonlinear transformations are usually applied to post-process speech features forming input to HMM based acoustic models. In this work, we experiment with three popular transforms: HLDA,MPE-HLDA and Region Dependent Linear Transforms (RDLT), which are trained jointly with the acoustic model to extract maximum of the discriminative information from the raw features and to represent it in a form suitable for the following GMM-HMM based acoustic model. We focus on multi-lingual environments, where limited resources are available for training recognizers of many languages. Using data from GlobalPhone database, we show that, under such restrictive conditions, the feature transformations can be advantageously shared across languages and robustly trained using data from several languages.

Published
2012
Pages
4885–4888
Proceedings
Proc. International Conference on Acoustics, Speech, and Signal Processing 2012
ISBN
978-1-4673-0044-5
Publisher
IEEE Signal Processing Society
Place
Kyoto
DOI
UT WoS
000312381404239
BibTeX
@inproceedings{BUT91480,
  author="Martin {Karafiát} and Miloš {Janda} and Jan {Černocký} and Lukáš {Burget}",
  title="Region Dependent Linear Transforms in Multilingual Speech Recognition",
  booktitle="Proc. International Conference on Acoustics, Speech, and Signal Processing 2012",
  year="2012",
  pages="4885--4888",
  publisher="IEEE Signal Processing Society",
  address="Kyoto",
  doi="10.1109/ICASSP.2012.6289014",
  isbn="978-1-4673-0044-5",
  url="http://www.fit.vutbr.cz/research/groups/speech/publi/2012/karafiat_icassp2012_0004885.pdf"
}
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