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Audible Paralinguistic Phenomena in Everyday Spoken Conversations: Evidence from the ORD Corpus Data

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Language, Music and Computing (LMAC 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 943))

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Abstract

Paralinguistic phenomena are non-verbal elements in conversation. Paralinguistic studies are usually based on audio or video recordings of spoken communication. In this article, we will show what kind of audible paralinguistic information may be obtained from the ORD speech corpus of everyday Russian discourse containing long-term audio recordings of conversations made in natural circumstances. This linguistic resource provides rich authentic data for studying the diversity of audible paralinguistic phenomena. The frequency of paralinguistic phenomena in everyday conversations has been calculated on the base of the annotated subcorpus of 187,600 tokens. The most frequent paralinguistic phenomena turned out to be: laughter, inhalation noise, cough, e-like and m-like vocalizations, tongue clicking, and the variety of unclassified non-verbal sounds (calls, exclamations, imitations by voice, etc.). The paper reports on distribution of paralinguistic elements, non-verbal interjections and hesitations in speech of different gender and age groups.

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Authors and Affiliations

  1. Saint Petersburg State University, Universitetskaya nab. 11, 199034, St. Petersburg, Russia

    Tatiana Sherstinova

  2. National Research University Higher School of Economics, 190068, St. Petersburg, Russia

    Tatiana Sherstinova

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  1. Tatiana Sherstinova
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Correspondence to Tatiana Sherstinova .

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Editors and Affiliations

  1. Saint Petersburg State University of Aerospace Instrumentation, Saint Petersburg, Russia

    Polina Eismont

  2. Saint Petersburg State University, St. Petersburg, Russia

    Olga Mitrenina

  3. Santa Clara University, Santa Clara, USA

    Asya Pereltsvaig

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Sherstinova, T. (2019). Audible Paralinguistic Phenomena in Everyday Spoken Conversations: Evidence from the ORD Corpus Data. In: Eismont, P., Mitrenina, O., Pereltsvaig, A. (eds) Language, Music and Computing. LMAC 2017. Communications in Computer and Information Science, vol 943. Springer, Cham. https://doi.org/10.1007/978-3-030-05594-3_11

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  • DOI: https://doi.org/10.1007/978-3-030-05594-3_11

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  • Online ISBN: 978-3-030-05594-3

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