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Estimating Stochasticity of Acoustic Signals

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Speech and Computer (SPECOM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8773))

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Abstract

In this paper, known methods for estimating the stochasticity of acoustic signals are compared, along with a new method based on adaptive signal filtration. Statistical simulation shows that the described method has better characteristics (lower variance and bias) than the other stochasticity measures. The parameters of the method, and their influence on performance, are investigated. Practical implementations for using the method are considered.

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Author information

Authors and Affiliations

  1. Speech Technology Center, Krasutskogo-4, St. Petersburg, 196084, Russia

    Sergei Aleinik

  2. ITMO University, 49 Kronverkskiy pr., St. Petersburg, 197101, Russia

    Sergei Aleinik & Oleg Kudashev

Authors
  1. Sergei Aleinik
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  2. Oleg Kudashev
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Editor information

Editors and Affiliations

  1. Speech and Multimodal Interfaces Laboratory, St. Petersburg Institute of Informatics and Automation of the Russian Academy of Sciences, 39, 14th line, 199178, St. Petersburg, Russia

    Andrey Ronzhin

  2. Institute of Applied and Mathematical Linguistics, Moscow State Linguistic University, 38, Ostozhenka, 119034, Moscow, Russia

    Rodmonga Potapova

  3. Faculty of Technical Sciences, University of Novi Sad, 6, Trg Dositeja Obradovića, 21000, Novi Sad, Serbia

    Vlado Delic

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© 2014 Springer International Publishing Switzerland

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Aleinik, S., Kudashev, O. (2014). Estimating Stochasticity of Acoustic Signals. In: Ronzhin, A., Potapova, R., Delic, V. (eds) Speech and Computer. SPECOM 2014. Lecture Notes in Computer Science(), vol 8773. Springer, Cham. https://doi.org/10.1007/978-3-319-11581-8_24

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  • DOI: https://doi.org/10.1007/978-3-319-11581-8_24

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11580-1

  • Online ISBN: 978-3-319-11581-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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