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International Conference on Speech and Computer

SPECOM 2016: Speech and Computer pp 596–603Cite as

Scores Calibration in Speaker Recognition Systems

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9811))

Abstract

It is well known that variability of speech signal quality affects the performance of speaker recognition systems. Difference in speech quality between enrollment and test utterances leads to shifting of scores and performance degradation. In order to improve the effectiveness of speaker recognition in these circumstances the scores calibration is required. Speech signal parameters that have a strong impact on speaker recognition performance are total speech duration, signal to noise ratio and reverberation time. Their variability leads to scores shifting and unreliable accept/reject decisions. In this paper we investigate the effects of speech duration variability on the calibration when enroll and test speech utterances originate from the same channel. An effective method of scores stabilization is also presented.

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Acknowledgments

This work was partially financially supported by the Government of the Russian Federation, Grant 074-U01.

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Authors and Affiliations

  1. ITMO University, Saint Petersburg, Russia

    Andrey Shulipa, Sergey Novoselov & Yuri Matveev

  2. Speech Technology Center, Saint Petersburg, Russia

    Sergey Novoselov & Yuri Matveev

Authors
  1. Andrey Shulipa
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  2. Sergey Novoselov
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  3. Yuri Matveev
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Corresponding author

Correspondence to Andrey Shulipa .

Editor information

Editors and Affiliations

  1. SPIIRAS , Saint-Petersburg, Russia

    Andrey Ronzhin

  2. Moscow State Linguistic University , Moscow, Russia

    Rodmonga Potapova

  3. Budapest University of Technology and Economics, Budapest, Hungary

    Géza Németh

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© 2016 Springer International Publishing Switzerland

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Shulipa, A., Novoselov, S., Matveev, Y. (2016). Scores Calibration in Speaker Recognition Systems. In: Ronzhin, A., Potapova, R., Németh, G. (eds) Speech and Computer. SPECOM 2016. Lecture Notes in Computer Science(), vol 9811. Springer, Cham. https://doi.org/10.1007/978-3-319-43958-7_72

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  • DOI: https://doi.org/10.1007/978-3-319-43958-7_72

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43957-0

  • Online ISBN: 978-3-319-43958-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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