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A Simple Way to Extract I-vector from Normalized Statastics

  • Conference paper
Biometric Recognition (CCBR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8833))

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Abstract

In the i-vector model, the utterance statistics are extracted from features using universal background model. The utterance is mapped to a vector in the total variability space, which is called i-vector. The total variability space provides a basis to obtain a low dimensional fixed-length representation of a speech utterance. But, the processing is complicated for the interweaving of the statistics and machine learning method. So, we considered separating them and proposed a simple way to extract i-vector by classical principal component analysis, factor analysis and independent component analysis from normalized statistics. The results on NIST 2008 telephone data show that the performance is very close to the traditional method and they can be improved obviously after score fusion.

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Author information

Authors and Affiliations

  1. School of Computer and Information Engineering, Jiangxi Normal University, Nanchang, China

    Zhenchun Lei, Jian Luo & Yingen Yang

Authors
  1. Zhenchun Lei
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  2. Jian Luo
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  3. Yingen Yang
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Editor information

Editors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, 100190, Beijing, China

    Zhenan Sun

  2. Institute of Computing Technology, Chinese Academy of Sciences, No.6 Kexueyuan South Road, P.O. Box 2704, 100190, HaiDian, Beijing, China

    Shiguang Shan

  3. School of Information Science and Engineering, Shenyang University of Technology, No.111, Shenliao West Road, Economic and Technological Development Zone, 110870, Shenyang, China

    Haifeng Sang  & Weiqi Yuan  & 

  4. Software Engineering Institute, Tsinghua University, No. 1 Tsinghua Yuan, Haidian District, 100084, Beijing, China

    Jie Zhou

  5. School of Computer Science and Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, 100191, Beijing, China

    Yunhong Wang

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© 2014 Springer International Publishing Switzerland

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Lei, Z., Luo, J., Yang, Y. (2014). A Simple Way to Extract I-vector from Normalized Statastics. In: Sun, Z., Shan, S., Sang, H., Zhou, J., Wang, Y., Yuan, W. (eds) Biometric Recognition. CCBR 2014. Lecture Notes in Computer Science, vol 8833. Springer, Cham. https://doi.org/10.1007/978-3-319-12484-1_41

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  • DOI: https://doi.org/10.1007/978-3-319-12484-1_41

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12483-4

  • Online ISBN: 978-3-319-12484-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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