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

  • Received Date: 1900-01-01
  • Rev Recd Date: 1900-01-01
  • Publish Date: 2010-01-05
  • 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.
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      沈阳化工大学材料科学与工程学院 沈阳 110142

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