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Individual Dimension Gaussian Mixture Model for Speaker Identification

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Advances in Biometric Person Authentication (IWBRS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3781))

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Abstract

In this paper, Individual Dimension Gaussian Mixture Model (IDGMM) is proposed for speaker identification. As to the training-purpose feature vector series of a certain register, its joint probability distribution function (PDF) of is modeled by the product of the PDF of each dimension (marginal PDF), the scalar-based Gaussian Mixture Model (GMM) serving as the marginal PDF. For a good discriminative capability, the decorrelation by Schmidt orthogonalization and the Mixture Component Number (MCN) decision are adopted during the train. A close-set text-independent speaker identification experiment is also given. The simulation result shows that the IDGMM accelerates the training process remarkably and maintains the discriminative capability in testing process.

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References

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Author information

Authors and Affiliations

  1. School of Communication and Information Engineering, Shanghai, China

    Chao Wang, Li Ming Hou & Yong Fang

Authors
  1. Chao Wang
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  2. Li Ming Hou
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  3. Yong Fang
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Editor information

Editors and Affiliations

  1. Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences,  

    Stan Z. Li

  2. National Laboratory of Pattern Recognition, Institute of Automation, CAS,  

    Zhenan Sun

  3. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  4. Exploratory Computer Vision Group, IBM T.J. Watson Research Center, 10598, Yorktown Heights, NY

    Sharath Pankanti

  5. CNRS LTCI/TSI Paris, 46 rue Barrault, 75634, Paris Cedex 13, France

    Gérard Chollet

  6. Biometrics Research Centre, Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong

    David Zhang

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© 2005 Springer-Verlag Berlin Heidelberg

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Wang, C., Hou, L.M., Fang, Y. (2005). Individual Dimension Gaussian Mixture Model for Speaker Identification. In: Li, S.Z., Sun, Z., Tan, T., Pankanti, S., Chollet, G., Zhang, D. (eds) Advances in Biometric Person Authentication. IWBRS 2005. Lecture Notes in Computer Science, vol 3781. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11569947_22

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  • DOI: https://doi.org/10.1007/11569947_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29431-3

  • Online ISBN: 978-3-540-32248-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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