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

DOI

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - 10.2991/iccia.2012.90
ID  - Zhang2014/05
ER  -