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Method of Speech Signal Structuring and Transforming for Biometric Personality Identification

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Data Stream Mining & Processing (DSMP 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1158))

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Abstract

This paper proposes a method for structuring and transforming a speech signal. For this, segmentation method, methods for determining the fundamental tone of the vocal segment and determining on its basis the boundaries of the quasiperiodic oscillations of the vocal segment, the geometric transformation of quasiperiodic oscillations of the vocal segment were suggested. The proposed segmentation of the speech signal uses statistical estimation of short-term energies, which allows the use of an adaptive threshold, thus increasing the vocal segments determination accuracy. The proposed definition of fundamental tone of the vocal segment uses bandpass filtering and statistical estimation of local extremum, which reduces computational complexity, and also reduces noise dependency and allows the use of an adaptive threshold, thus increasing the accuracy of determining the fundamental tone and the boundaries of quasiperiodic oscillations of the vocal segment. The proposed geometric transformation of quasiperiodic oscillations of the vocal segment allows you to transform quasiperiodic oscillations to a single amplitude-time window, which allows you to form patterns of the vocal segment, taking into account its structure. A method for determining a model structure for transforming speech signal patterns is proposed, which is based on a statistical evaluation of the quality of the transforming, which provides a high degree of compression and the speech signal identification.

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Authors and Affiliations

  1. Cherkasy State Technological University, Cherkasy, Ukraine

    Eugene Fedorov, Tetyana Utkina, Olga Nechyporenko & Yaroslav Korpan

Authors
  1. Eugene Fedorov
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  2. Tetyana Utkina
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  3. Olga Nechyporenko
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  4. Yaroslav Korpan
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Corresponding author

Correspondence to Eugene Fedorov .

Editor information

Editors and Affiliations

  1. Department of Informatics, Univerzita Jana Evangelisty PurkynÄ› v ĂšstĂ­ nad Labem, ĂšstĂ­ nad Labem, Czech Republic

    Sergii Babichev

  2. GeoGuard, Kharkiv, Ukraine

    Dmytro Peleshko

  3. Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

    Olena Vynokurova

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Fedorov, E., Utkina, T., Nechyporenko, O., Korpan, Y. (2020). Method of Speech Signal Structuring and Transforming for Biometric Personality Identification. In: Babichev, S., Peleshko, D., Vynokurova, O. (eds) Data Stream Mining & Processing. DSMP 2020. Communications in Computer and Information Science, vol 1158. Springer, Cham. https://doi.org/10.1007/978-3-030-61656-4_20

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  • DOI: https://doi.org/10.1007/978-3-030-61656-4_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61655-7

  • Online ISBN: 978-3-030-61656-4

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