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On the Impact of Non-speech Sounds on Speaker Recognition

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Text, Speech and Dialogue (TSD 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7499))

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Abstract

This paper investigates the impact of non-speech sounds on the performance of speaker recognition. Various experiments were conducted to check what the accuracy of speaker classification would be if non-speech sounds, such as breaths, were removed from the training and/or testing speech. Experiments were run using the GMM-UBM algorithm and speech taken from the TIMIT speech corpus, either original or transcoded using the G.711 or GSM 06.10 codecs. The results show a remarkable contribution of non-speech sounds to the overall speaker recognition performance.

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Author information

Authors and Affiliations

  1. Institute of Telecommunication, Warsaw University of Technology, ul. Nowowiejska 15/19, 00-665, Warsaw, Poland

    Artur Janicki

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  1. Artur Janicki
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Editor information

Editors and Affiliations

  1. Faculty of Informatics, Department of Computer Graphics and Design, Masaryk University, Botanická 68a, 602 00, Brno, Czech Republic

    Petr Sojka

  2. Faculty of Informatics, Department of Information Technologies, Masaryk University, Botanická 68a, 602 00, Brno, Czech Republic

    Aleš Horák , Ivan Kopeček  & Karel Pala ,  & 

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© 2012 Springer-Verlag Berlin Heidelberg

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Janicki, A. (2012). On the Impact of Non-speech Sounds on Speaker Recognition. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2012. Lecture Notes in Computer Science(), vol 7499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32790-2_69

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  • DOI: https://doi.org/10.1007/978-3-642-32790-2_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32789-6

  • Online ISBN: 978-3-642-32790-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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