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.
Original languageEnglish
Title of host publicationLanguage, Music and Computing
Subtitle of host publicationConference proceedings LMAC 2017
EditorsPolina Eismont, Olga Mitrenina, Asya Pereltsvaig
Place of PublicationCham
PublisherSpringer Nature
Pages131–145
ISBN (Electronic)978303055943
ISBN (Print)978303055936
DOIs
StatePublished - 2019
EventSecond International Workshop on Language, Music and Computing - St. Petersburg, Russian Federation
Duration: 17 Apr 201719 Apr 2017

Publication series

NameCommunications in Computer and Information Science
Volume943
ISSN (Print)1865-0929

Conference

ConferenceSecond International Workshop on Language, Music and Computing
Abbreviated titleLMAC 2017
Country/TerritoryRussian Federation
CitySt. Petersburg
Period17/04/1719/04/17

    Research areas

  • Paralinguistics, Audible paralinguistic phenomena, vocalizations, Everyday conversation, Spoken interaction, speech corpus, Russian language, Laughter, Interjections, Hesitations, Fillers, Gender, Age

    Scopus subject areas

  • Information Systems
  • Language and Linguistics

ID: 51201302