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Text-independent speaker identification based on spectral weighting functions

  • Text-independent Speaker Authentication
  • Conference paper
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Book cover Audio- and Video-based Biometric Person Authentication (AVBPA 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1206))

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Abstract

This paper introduces a novel approach to extract the speaker feature for textindependent speaker identification, the procedure to determine spectral weighting functions used in modeling the effect of the frequency selectivity and masking properties of human cochlea is systematically demonstrated. The modified LPC-derived cepstral coefficients based on spectral weighting functions are used in text-independent speaker identification to emphasize the individual information in the speech. The VQ technique is used as a classifier, experiment results obtained by the proposed approach in this paper are compared with those of LPC and PLP based method on a close set of 300 speakers, the results have shown that the proposed approach is robust against the intraspeaker and the interspeaker variations.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Harbin Institute of Technology, 150001, Harbin, China

    Ma Jiyong & Gao Wen

Authors
  1. Ma Jiyong
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  2. Gao Wen
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Editor information

Josef Bigün Gérard Chollet Gunilla Borgefors

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© 1997 Springer-Verlag Berlin Heidelberg

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Jiyong, M., Wen, G. (1997). Text-independent speaker identification based on spectral weighting functions. In: Bigün, J., Chollet, G., Borgefors, G. (eds) Audio- and Video-based Biometric Person Authentication. AVBPA 1997. Lecture Notes in Computer Science, vol 1206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0016004

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  • DOI: https://doi.org/10.1007/BFb0016004

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62660-2

  • Online ISBN: 978-3-540-68425-1

  • eBook Packages: Springer Book Archive

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