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  1. Gender Differences in the Recognition of Vocal Emotions.Adi Lausen & Annekathrin Schacht - 2018 - Frontiers in Psychology 9:359771.
    The conflicting findings from the few studies conducted with regard to gender differences in the recognition of vocal expressions of emotion have left the exact nature of these differences unclear. Several investigators have argued that a comprehensive understanding of gender differences in vocal emotion recognition can only be achieved by replicating these studies while accounting for influential factors such as stimulus type, gender-balanced samples, number of encoders, decoders and emotional categories. This study aimed to account for these factors by investigating (...)
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  • Cross-Cultural Emotion Recognition and In-Group Advantage in Vocal Expression: A Meta-Analysis.Petri Laukka & Hillary Anger Elfenbein - 2020 - Emotion Review 13 (1):3-11.
    Most research on cross-cultural emotion recognition has focused on facial expressions. To integrate the body of evidence on vocal expression, we present a meta-analysis of 37 cross-cultural studies...
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  • Detecting emotion in speech expressing incongruent emotional cues through voice and content: investigation on dominant modality and language.Mariko Kikutani & Machiko Ikemoto - 2022 - Cognition and Emotion 36 (3):492-511.
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  • Exploring the Effects of Personality Traits on the Perception of Emotions From Prosody.Desire Furnes, Hege Berg, Rachel M. Mitchell & Silke Paulmann - 2019 - Frontiers in Psychology 10.
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  • Electroencephalographic Correlate of Mexican Spanish Emotional Speech Processing in Autism Spectrum Disorder: To a Social Story and Robot-Based Intervention.Mathilde Marie Duville, Luz Maria Alonso-Valerdi & David I. Ibarra-Zarate - 2021 - Frontiers in Human Neuroscience 15.
    Socio-emotional impairments are key symptoms of Autism Spectrum Disorders. This work proposes to analyze the neuronal activity related to the discrimination of emotional prosodies in autistic children as follows. Firstly, a database for single words uttered in Mexican Spanish by males, females, and children will be created. Then, optimal acoustic features for emotion characterization will be extracted, followed of a cubic kernel function Support Vector Machine in order to validate the speech corpus. As a result, human-specific acoustic properties of emotional (...)
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