Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)

Code-switching Speech Detection Method by Combination of Language and Acoustic Information

Authors
Hongji Zhang
Corresponding Author
Hongji Zhang
Available Online May 2014.
DOI
https://doi.org/10.2991/iccia.2012.90How to use a DOI?
Keywords
code-switching speech, acoustic model, language identification, support vector machine
Abstract
In this paper, we propose a new speech detection method to English-Mandarin code-switching speech. Unlike previous methods, in this method we first train a support vector machine (SVM) model based on feature parameters and Gaussian Mixture Model (GMM) , then integrate the language identification (LID) information based on SVM model and acoustic information into the decoding process. Lastly, we develop a prototype system to present the method. Experiments proved that our method we can improve the accurancy of code-switching speech recognition at a certain degree compared with previous methods.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
Part of series
Advances in Intelligent Systems Research
Publication Date
May 2014
ISBN
978-94-91216-41-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/iccia.2012.90How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Hongji Zhang
PY  - 2014/05
DA  - 2014/05
TI  - Code-switching Speech Detection Method by Combination of Language and Acoustic Information
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 372
EP  - 375
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.90
DO  - https://doi.org/10.2991/iccia.2012.90
ID  - Zhang2014/05
ER  -