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Detecting Filled Pauses and Lengthenings in Russian Spontaneous Speech Using SVM

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Speech and Computer (SPECOM 2016)

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

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Abstract

Spontaneous speech differs from any other type of speech in many ways. And the presence of speech disfluencies is its prominent characteristic. These phenomena are important feature in human-human communication and at the same time a challenging obstacle for the speech processing tasks. This paper reports the experiment results on automatic detection of filled pauses and sound lengthenings basing on the automatically extracted acoustic features. We have performed machine learning experiments using support vector machine (SVM) classifier on the mixed and quality diverse corpus of Russian spontaneous speech. We applied Gaussian filtering and morphological opening to post-process the probability estimates from an SVM classifier. As the result we achieved F1–score of 0.54, with precision and recall being 0.55 and 0.53 respectively.

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Acknowledgments

This research is supported by the grant of Russian Foundation for Basic Research (project No 15-06-04465) and by the Council for Grants of the President of the Russian Federation (project No. MK-5209.2015.8).

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Authors and Affiliations

  1. SPIIRAS, St. Petersburg, Russia

    Vasilisa Verkhodanova & Vladimir Shapranov

Authors
  1. Vasilisa Verkhodanova
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  2. Vladimir Shapranov
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Corresponding author

Correspondence to Vasilisa Verkhodanova .

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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Verkhodanova, V., Shapranov, V. (2016). Detecting Filled Pauses and Lengthenings in Russian Spontaneous Speech Using SVM. 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_26

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  • DOI: https://doi.org/10.1007/978-3-319-43958-7_26

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  • 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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