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Annotation and Personality: Individual Differences in Sentence Boundary Detection

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Speech and Computer (SPECOM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8773))

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Abstract

The paper investigates the relationships between personality traits and expert manual annotation of unscripted speech. The analysis is based on the results of a psycholinguistic experiment in which the participants were asked to annotate sentence boundaries in transcriptions of Russian spoken monologues. Personality traits were measured using the Eysenck Personality Inventory and the Five Factor Personality Questionnaire. A multiple regression model showed that the traits measured by the Five Factor Personality Questionnaire along the scales ‘unemotionality vs. emotionality’ and ‘practicality vs. playfulness’ had significant effect on the average sentence length.

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Author information

Authors and Affiliations

  1. Department of Russian, St. Petersburg State University, 11 Universitetskaya emb., 199034, St. Petersburg, Russia

    Anton Stepikhov

  2. Educational Testing Service, 660 Rosedale Rd, MS 11-R, Princeton, NJ, 08541, USA

    Anastassia Loukina

Authors
  1. Anton Stepikhov
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  2. Anastassia Loukina
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Editor information

Editors and Affiliations

  1. Speech and Multimodal Interfaces Laboratory, St. Petersburg Institute of Informatics and Automation of the Russian Academy of Sciences, 39, 14th line, 199178, St. Petersburg, Russia

    Andrey Ronzhin

  2. Institute of Applied and Mathematical Linguistics, Moscow State Linguistic University, 38, Ostozhenka, 119034, Moscow, Russia

    Rodmonga Potapova

  3. Faculty of Technical Sciences, University of Novi Sad, 6, Trg Dositeja Obradovića, 21000, Novi Sad, Serbia

    Vlado Delic

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© 2014 Springer International Publishing Switzerland

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Stepikhov, A., Loukina, A. (2014). Annotation and Personality: Individual Differences in Sentence Boundary Detection. In: Ronzhin, A., Potapova, R., Delic, V. (eds) Speech and Computer. SPECOM 2014. Lecture Notes in Computer Science(), vol 8773. Springer, Cham. https://doi.org/10.1007/978-3-319-11581-8_13

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  • DOI: https://doi.org/10.1007/978-3-319-11581-8_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11580-1

  • Online ISBN: 978-3-319-11581-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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