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SNR Estimation Based on Adaptive Signal Decomposition for Quality Evaluation of Speech Enhancement Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9319))

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Abstract

This paper presents a new method for estimating signal-to-noise ratio based on adaptive signal decomposition. Statistical simulation shows that the proposed method has lower variance and bias than the known signal-to-noise ratio measures. We discuss the parameters and characteristics of the proposed method and its practical implementation.

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Acknowledgements

This work was financially supported by the Ministry of Education and Science of the Russian Federation, contract 14.575.21.0033 (RFMEFI57514X0033), and by the Government of the Russian Federation, Grant 074-U01.

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Authors and Affiliations

  1. ITMO University, 49 Kronverkskiy Pr., St. Petersburg, 197101, Russia

    Sergei Aleinik & Mikhail Stolbov

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

    Mikhail Stolbov

Authors
  1. Sergei Aleinik
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  2. Mikhail Stolbov
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Corresponding author

Correspondence to Sergei Aleinik .

Editor information

Editors and Affiliations

  1. SPIIRAS, Saint-Petersburg, Russia

    Andrey Ronzhin

  2. Moscow State Linguistic University, Moscow, Russia

    Rodmonga Potapova

  3. University of Patras, Patras, Greece

    Nikos Fakotakis

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© 2015 Springer International Publishing Switzerland

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Aleinik, S., Stolbov, M. (2015). SNR Estimation Based on Adaptive Signal Decomposition for Quality Evaluation of Speech Enhancement Algorithms. In: Ronzhin, A., Potapova, R., Fakotakis, N. (eds) Speech and Computer. SPECOM 2015. Lecture Notes in Computer Science(), vol 9319. Springer, Cham. https://doi.org/10.1007/978-3-319-23132-7_45

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  • DOI: https://doi.org/10.1007/978-3-319-23132-7_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23131-0

  • Online ISBN: 978-3-319-23132-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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