Evidence for cultural dialects in vocal emotion expression: Acoustic classification within and across five nations.

Abstract

The possibility of cultural differences in the fundamental acoustic patterns used to express emotion through the voice is an unanswered question central to the larger debate about the universality versus cultural specificity of emotion. This study used emotionally inflected standard-content speech segments expressing 11 emotions produced by 100 professional actors from 5 English-speaking cultures. Machine learning simulations were employed to classify expressions based on their acoustic features, using conditions where training and testing were conducted on stimuli coming from either the same or different cultures. A wide range of emotions were classified with above-chance accuracy in cross-cultural conditions, suggesting vocal expressions share important characteristics across cultures. However, classification showed an in-group advantage with higher accuracy in within- versus cross-cultural conditions. This finding demonstrates cultural differences in expressive vocal style, and supports the dialect theory of emotions according to which greater recognition of expressions from in-group members results from greater familiarity with culturally specific expressive styles.

The influence of language and culture on the understanding of vocal emotions

“…Altrov 2013, Bryant and Barrett 2008, and Jürgens et al 2013). According to Laukka et al (2014) as well as to Scherer et al (2011) the universality of emotions is supported by the fact that if a listening task requires the classification of emotions of any culture into predetermined categories, recognition accuracy is b etter than chance probability. However, research has revealed that emotion expressions are better identified by members of one's own culture (so-called in-group advantage).…”

“…However, research has revealed that emotion expressions are better identified by members of one's own culture (so-called in-group advantage). A poorer performance in identifying the emotion expressions of other cultures may be due to cultural differences in emotion expression (Elfenbein 2013, andLaukka et al 2014). True, most proof of the universality of emotion recognition has been obtained from cross-cultural studies of the face, while cross-cultural studies of the identification of vocal emotions in speech are much rarer (see Uskul 2014, andPell et al 2009).…”

“…The British participants manifested in-group advantage in recogni zing all emotions except joy and neutrality; the Chinese participants showed in-group advantage in recognizing all emotions except fear and sadness. Laukka et al (2014) used a machine learning method to classify, on the basis of acoustic features, eleven emotions expressed with a different intensity in a sentence with a constant verbal content by 100 actors from five English-speaking countries. Experiments were performed in conditions where classifier programmes were trained on stimuli from either the same or different culture vis-à-vis the stimuli subsequently used in the testing phase.…”

Experimental Approaches to Socio‐Linguistics: Usage and Interpretation of Non‐Verbal and Verbal Expressions in Cross‐ Cultural Communication

“…One study with machine learning simulation aims to make the first attempt to isolate the impact of physical properties of auditory stimuli from that of cultural norms that affect the perceptual-acoustic classification of vocal expressions [34]. In this study, acoustic features were extracted from short utterances expressing 11 typical emotions (anger, contempt, fear, happiness, interest, neutral, sexual lust, pride, relief, sadness and shame), produced by 100 professional speakers from 5 English-speaking cultures (Australia, India, Kenya, Singapore and USA).…”

Revisiting diversity: cultural variation reveals the constructed nature of emotion perception

“… ii When universality is assumed, this modulation is proposed to occur via culturally set rules for what (and when) inborn expressions are appropriate to display, i.e., display rules [54], or via culturally acquired accents that modulate the form of innate facial actions [55] and vocalizations [56]. …”