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

Adi Lausen () and Kurt Hammerschmidt
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Adi Lausen: University of Goettingen
Kurt Hammerschmidt: University of Goettingen

Palgrave Communications, 2020, vol. 7, issue 1, 1-17

Abstract: 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.

Date: 2020
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DOI: 10.1057/s41599-020-0499-z

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