ZHANG Weiqiang, HOU Tao, LIU Jia. Discriminative Score Fusion for LanguageIdenti¯cation[J]. Chinese Journal of Electronics, 2010, 19(1): 124-128.
Citation: ZHANG Weiqiang, HOU Tao, LIU Jia. Discriminative Score Fusion for LanguageIdenti¯cation[J]. Chinese Journal of Electronics, 2010, 19(1): 124-128.

Discriminative Score Fusion for LanguageIdenti¯cation

More Information
  • Received Date: December 31, 1899
  • Revised Date: December 31, 1899
  • Published Date: January 04, 2010
  • Language identi¯cation (LID) has received
    increasing interests in the speech signal processing com-
    munity. With the rapid development of LID technologies,
    how to fuse the score of multi-systems is growing to be a
    researching focus. In this paper, we proposed a discrimina-
    tive framework for LID score fusion. The Heteroscedastic
    linear discriminate analysis (HLDA) technology is used for
    dimension reduction and de-correlation, and the Gaussian
    mixture model (GMM) trained with Maximum mutual in-
    formation (MMI) criteria is used as classi¯er. Experiments
    show that the proposed method can improve the perfor-
    mance signi¯cantly. By score fusion of ¯ve systems, we
    achieve average cost of 2.10% for 30s trials on the 2007
    NIST language recognition evaluation databases.

Catalog

    Article Metrics

    Article views (1363) PDF downloads (1243) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return