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Emotion recognition and confidence ratings predicted by vocal stimulus type and prosodic parameters

Author

Listed:
  • Adi Lausen

    (University of Goettingen
    University of Essex)

  • Kurt Hammerschmidt

    (University of Goettingen
    Leibniz ScienceCampus “Primate Cognition”)

Abstract

Human speech expresses emotional meaning not only through semantics, but also through certain attributes of the voice, such as pitch or loudness. In investigations of vocal emotion recognition, there is considerable variability in the types of stimuli and procedures used to examine their influence on emotion recognition. In addition, accurate metacognition was argued to promote correct and confident interpretations in emotion recognition tasks. Nevertheless, such associations have rarely been studied previously. We addressed this gap by examining the impact of vocal stimulus type and prosodic speech attributes on emotion recognition and a person’s confidence in a given response. We analysed a total of 1038 emotional expressions according to a baseline set of 13 prosodic acoustic parameters. Results showed that these parameters provided sufficient discrimination between expressions of emotional categories to permit accurate statistical classification. Emotion recognition and confidence judgments were found to depend on stimulus material as they could be reliably predicted by different constellations of acoustic features. Finally, results indicated that listeners’ accuracy and confidence judgements were significantly higher for affect bursts than speech-embedded stimuli and that the correct classification of emotional expressions elicited increased confidence judgements. Together, these findings show that vocal stimulus type and prosodic attributes of speech strongly influence emotion recognition and listeners’ confidence in these given responses.

Suggested Citation

  • Adi Lausen & Kurt Hammerschmidt, 2020. "Emotion recognition and confidence ratings predicted by vocal stimulus type and prosodic parameters," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-17, December.
    • Handle: RePEc:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-0499-z
    DOI: 10.1057/s41599-020-0499-z
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    References listed on IDEAS

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    1. Annett Schirmer, 2010. "Mark My Words: Tone of Voice Changes Affective Word Representations in Memory," PLOS ONE, Public Library of Science, vol. 5(2), pages 1-9, February.
    2. Simon Schaerlaeken & Didier Grandjean, 2018. "Unfolding and dynamics of affect bursts decoding in humans," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-21, October.
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    Cited by:

    1. Mathilde Marie Duville & Luz María Alonso-Valerdi & David I. Ibarra-Zarate, 2021. "Mexican Emotional Speech Database Based on Semantic, Frequency, Familiarity, Concreteness, and Cultural Shaping of Affective Prosody," Data, MDPI, vol. 6(12), pages 1-34, December.

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