Emotion Inferences from Vocal Expression Correlate Across Languages and Cultures

By Klaus R. Scherer, R. Banse, H. Wallbott. 2001

780 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology, Language and Linguistics

View Paper: https://www.semanticscholar.org/paper/818cfcf6afabe5bd5f44c49686d0f20ba0b2c3d2

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Citations in the corpus

CREMA-D: Crowd-sourced Emotional Multimodal Actors Dataset (2014, background): “Parallel research exists in vocal expression [4], [5].”
On the universality and cultural specificity of emotion recognition: a meta-analysis. (2002, background): “Scherer, Banse, and Wallbott (2001) also argued that characteristic suprasegmental cues such as intonation contours and rhythm can vary across language families and may be difficult for outsiders to decode.”
AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition (2019, result): “Matching with similar results in the literature [21, 56], all entrants in the AVEC 2018 CES observed a drop in system performance when testing on the Hungarian data [27, 76, 82].”
Vocal Emotion Recognition Across Disparate Cultures (2008, background): “For example, Scherer et al. (2001) found that judges in nine countries reliably recognized four different emotions better than chance from content-free speech (i.e., selected combinations of meaningless syllables from six Indo-European languages).”
An Evolutionary Approach to Emotional Communication (2013, background): “However the ultimate question of how thesemechanismsmaintain the stability of emotional communication has received less attention.”
Recognizing Emotions in a Foreign Language (2009, background): “Our data simultaneously highlight an in-group advantage for recognizing vocallyexpressed emotions presented in a listener’s native language (Albas et al. 1976; Scherer et al. 2001; Thompson and Balkwill 2006; Van Bezooijen et al. 1983).”
Assessing the Ability to Recognize Facial and Vocal Expressions of Emotion: Construction and Validation of the Emotion Recognition Index (2011, methodology): “The vocal stimuli were selected from a vocal expression corpus that had been created for a large cross-cultural study of vocal emotion recognition (the International Study of Vocal Emotion Expression [ISVEE]; see Scherer et al. 2001).”
Assessing Emotional Intelligence (2009, methodology): “The outstanding EI test was the Voices performance task (Scherer et al., 2001) explaining 10% of the variance in the BEB criterion, and continuing to explain 10% of the variance after controlling for personality and IQ.”