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Proceedings Paper

Automatic language identification based on Gaussian mixture model and universal background model
Author(s): Dan Qu; Bingxi Wang; Xin Wei
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Paper Abstract

When compared with speech technologies in speech processing, automatic language identification is a relatively new yet difficult problem. In this paper, a language identification algorithm is provided and some experiments are conducted using OGI multi-language telephone speech corpus (OGI-TS). Then experiments results are described. It is shown that GMM-UBM is another efficient method to language identification problems.

Paper Details

Date Published: 25 September 2003
PDF: 4 pages
Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.538980
Show Author Affiliations
Dan Qu, Zhengzhou Information Engineering Univ. (China)
Bingxi Wang, Zhengzhou Information Engineering Univ. (China)
Xin Wei, Zhengzhou Information Engineering Univ. (China)


Published in SPIE Proceedings Vol. 5286:
Third International Symposium on Multispectral Image Processing and Pattern Recognition
Hanqing Lu; Tianxu Zhang, Editor(s)

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