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

Lausen, Adi; Hammerschmidt, Kurt

doi:10.1057/s41599-020-0499-z

Cited by 34 publications

(29 citation statements)

References 86 publications

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“…Present acoustic measures and lexical norms are sufficient for inferring and predicting threat comprehension, but they cannot provide a full account of the prosody and semantics of anger, which may be composed by a myriad of features establishing more complex and nuanced relations (Lausen and Hammerschmidt, 2020). Having stated this, the present analogy between bidimensional features of prosody and semantics is further confirmed by SAM and classification tasks.…”

Section: Discussionmentioning

confidence: 79%

“…Hence, the present model should be understood as derived from more complex previous models (e.g. Banse and Scherer, 1996;Hammerschmidt and Jürgens, 2007;Lausen and Hammerschmidt, 2020), in such a way that it retains inferential capacity (though not fully descriptive) and facilitates prediction. This could provide useful insights into emotional expression/comprehension, which may be extended from threat or 'hot anger' to other emotions.…”

Section: Introductionmentioning

confidence: 99%

“…Prosody is understood as the variation and combination of suprasegmental features, such as sound intensity, rhythm or pitch; combination and variation which, together with semantic content, can be intended for the communication of emotion (Lausen and Hammerschmidt, 2020). Thus, the comprehension of prosody might depend upon contrasts between and presence/absence of several features, which have been adjusted by the speaker to convey a specific emotion (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Bidimensional Features of Prosody and Semantic are Sufficient for Inferring and Predicting Threatening Speech Comprehension

Moreno¹,

Vinson²

2021

Preprint

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The present study investigates how variation in acoustic measures and lexical semantic properties affect the comprehension of threatening speech. Two experiments were conducted in British English, where participants had to rate the threat of three types of sentences: sentences neutral in prosody and semantics, sentences containing only prosodic threat, and sentences containing only semantic threat. They also rated the sentences for arousal and valence, and categorised them by type of emotional expression. Threat ratings were analysed via Bayesian ordered-logistic regressions using acoustic measures and affective norms as regressors. Classification was assessed via simple Bayesian categorical (Dirichlet prior) models. Acoustic properties of stimuli were compared through a Bayesian method for comparison of means to test whether neutral stimuli differ, on average, from their threatening counterparts. Acoustic but not semantic properties affected ratings of threatening prosody (increased pitch and decreased voice quality predicting increased threat), while the reverse was true for ratings of threatening semantics (increased arousal and decreased valence predicting increased threat). Using data from the first speaker (first experiment) the models were able to predict ratings given to sentences produced by the second speaker (second experiment). Furthermore, threatening sentences of both types tended to be categorized as angry or enraged. These results are interpreted as supporting the sufficiency of the selected measures (pitch, voice quality, arousal, valence) to characterise threat. Although multidimensional models may be better suited for describing threatening prosody/semantics, the present approach demonstrates that selected bidimensional features are sufficient to identify and predict threat comprehension efficiently and accurately.

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Section: Discussionmentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bidimensional Features of Prosody and Semantic are Sufficient for Inferring and Predicting Threatening Speech Comprehension

Moreno¹,

Vinson²

2021

Preprint

View full text Add to dashboard Cite

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“…Even though arguments for superior decoding of emotions from nonverbal vocalisations over speech prosody have been put forward, there is little research formally testing this notion. Studies conducted to date have found that negative emotions are recognised more accurately (Hawk, van Kleef, Fischer, & Schalk, 2009;Lausen & Hammerschmidt, 2020;Sauter, 2007) and rapidly (Castiajo & Pinheiro, 2019;Pell, 2015) from nonverbal vocalisations compared to speech prosody. For positive emotions, this perception advantage of nonverbal vocalisations has been tested for happiness/joy and pride, yet it is not established whether it generalises to other positive emotions.…”

Section: Nonverbal Vocalisations Vs Speech Prosodymentioning

confidence: 99%

Superior communication of positive emotions through nonverbal vocalisations compared to speech prosody

Kamiloglu¹,

Boateng²,

Balabanova³

et al. 2020

Preprint

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The human voice communicates emotion through two different types of vocalisations: nonverbal vocalisations (brief non-linguistic sounds like laughs) and speech prosody (tone of voice). Research examining recognisability of emotions from the voice has mostly focused on either nonverbal vocalisations or speech prosody, and included few categories of positive emotions. In two preregistered experiments, we compare human listeners’ (total n = 400) recognition performance for 22 positive emotions from nonverbal vocalisations (n = 880) to that from speech prosody (n = 880). The results show that listeners were more accurate in recognising most positive emotions from nonverbal vocalisations compared to prosodic expressions. Furthermore, acoustic classification experiments with machine learning models demonstrated that positive emotions are expressed with more distinctive acoustic patterns for nonverbal vocalisations as compared to speech prosody. Overall, the results suggest that vocal expressions of positive emotions are more distinctive in terms of acoustic patterns when expressed as nonverbal vocalisations than as speech prosody, resulting in superior recognition of positive emotions from nonverbal vocalisations.

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“…Even though arguments for enhanced communication of emotions via nonverbal vocalizations as compared to speech prosody have been put forward, there is little research formally testing this notion. Studies conducted to date have found that negative emotions are recognized more accurately (Hawk et al, 2009 ; Lausen & Hammerschmidt, 2020 ; Sauter, 2007 ) and rapidly (Castiajo & Pinheiro, 2019 ; Pell et al, 2015 ; Schaerlaeken & Grandjean, 2018 ) from nonverbal vocalizations compared to speech prosody. For positive emotions, this perception advantage of nonverbal vocalizations has been tested for happiness/joy and pride, yet it is not established whether it generalizes to other positive emotions.…”

Section: Introductionmentioning

confidence: 99%

Superior Communication of Positive Emotions Through Nonverbal Vocalisations Compared to Speech Prosody

et al. 2021

View full text Add to dashboard Cite

The human voice communicates emotion through two different types of vocalizations: nonverbal vocalizations (brief non-linguistic sounds like laughs) and speech prosody (tone of voice). Research examining recognizability of emotions from the voice has mostly focused on either nonverbal vocalizations or speech prosody, and included few categories of positive emotions. In two preregistered experiments, we compare human listeners’ (total n = 400) recognition performance for 22 positive emotions from nonverbal vocalizations (n = 880) to that from speech prosody (n = 880). The results show that listeners were more accurate in recognizing most positive emotions from nonverbal vocalizations compared to prosodic expressions. Furthermore, acoustic classification experiments with machine learning models demonstrated that positive emotions are expressed with more distinctive acoustic patterns for nonverbal vocalizations as compared to speech prosody. Overall, the results suggest that vocal expressions of positive emotions are communicated more successfully when expressed as nonverbal vocalizations compared to speech prosody.

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

Cited by 34 publications

References 86 publications

Bidimensional Features of Prosody and Semantic are Sufficient for Inferring and Predicting Threatening Speech Comprehension

Bidimensional Features of Prosody and Semantic are Sufficient for Inferring and Predicting Threatening Speech Comprehension

Superior communication of positive emotions through nonverbal vocalisations compared to speech prosody

Superior Communication of Positive Emotions Through Nonverbal Vocalisations Compared to Speech Prosody

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