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Speaking Style Based Apparent Personality Recognition

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Speech and Computer (SPECOM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11658))

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Abstract

In this study, we investigate the problem of apparent personality recognition using person’s voice, or more precisely, the way he or she speaks. Based on the style transfer idea in deep neural net image processing, we developed a system capable of speaking style extraction from recorded speech utterances, which then uses this information to estimate the so called Big-Five personality traits. The latent speaking style space is represented by the Gram matrix of convoluted acoustic features. We used a database with labels of personality traits perceived by other people (first impression). The experimental results showed that the proposed system achieves state of the art results for the task of audio based apparent personality recognition.

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Author information

Authors and Affiliations

  1. The University of Aizu, Fukushima, Japan

    Jianguo Yu & Konstantin Markov

  2. SPIIRAS, St. Petersburg, Russia

    Alexey Karpov

Authors
  1. Jianguo Yu
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  2. Konstantin Markov
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  3. Alexey Karpov
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Corresponding authors

Correspondence to Jianguo Yu , Konstantin Markov or Alexey Karpov .

Editor information

Editors and Affiliations

  1. Utrecht University, Utrecht, The Netherlands

    Albert Ali Salah

  2. St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg, Russia

    Alexey Karpov

  3. Moscow State Linguistic University, Moscow, Russia

    Rodmonga Potapova

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Yu, J., Markov, K., Karpov, A. (2019). Speaking Style Based Apparent Personality Recognition. In: Salah, A., Karpov, A., Potapova, R. (eds) Speech and Computer. SPECOM 2019. Lecture Notes in Computer Science(), vol 11658. Springer, Cham. https://doi.org/10.1007/978-3-030-26061-3_55

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  • DOI: https://doi.org/10.1007/978-3-030-26061-3_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26060-6

  • Online ISBN: 978-3-030-26061-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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