Publication detail

Region Dependent Linear Transforms in Multilingual Speech Recognition

KARAFIÁT, M. JANDA, M. ČERNOCKÝ, J. BURGET, L.

Original Title

Region Dependent Linear Transforms in Multilingual Speech Recognition

Type

conference paper

Language

English

Original 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.

Keywords

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

Authors

KARAFIÁT, M.; JANDA, M.; ČERNOCKÝ, J.; BURGET, L.

RIV year

2012

Released

25. 3. 2012

Publisher

IEEE Signal Processing Society

Location

Kyoto

ISBN

978-1-4673-0044-5

Book

Proc. International Conference on Acoustics, Speech, and Signal Processing 2012

Pages from

4885

Pages to

4888

Pages count

4

URL

http://www.fit.vutbr.cz/research/groups/speech/publi/2012/karafiat_icassp2012_0004885.pdf

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"
}