A questionnaire was sent to a random sample of 500 community living older adults in Sweden (aged 65-75 years). The questionnaire assessed uses of music in everyday life: frequency of listening, ...situations where music is encountered, emotional responses to music, and motives for listening (i.e., listening strategies). Also, different facets of psychological well-being (e.g., affective well-being, life satisfaction, and eudaimonic well-being) and selected background variables (e.g., education level, health status, activity level, and Big-5 personality characteristics) were assessed. Results showed that listening to music is a common leisure activity encountered in many everyday situations, and that listening to music is a frequent source of positive emotions for older adults. Also, the participants reported using a variety of listening strategies related to emotional functions (e.g., pleasure, mood regulation, and relaxation) and issues of identity, belonging, and agency. The associations between listening strategies and well-being were explored through correlation and multiple regression analyses where the influence of background variables was controlled for. Health status and personality were the most important predictors of well-being, but some listening strategies were also significantly associated with psychological well-being. The results give important insights into older adults' uses of music in everyday life and give clues regarding possible relationships between musical activities and well-being.PUBLICATION ABSTRACT
Emotional vocalizations are central to human social life. Recent studies have documented that people recognize at least 13 emotions in brief vocalizations. This capacity emerges early in development, ...is preserved in some form across cultures, and informs how people respond emotionally to music. What is poorly understood is how emotion recognition from vocalization is structured within what we call a semantic space, the study of which addresses questions critical to the field: How many distinct kinds of emotions can be expressed? Do expressions convey emotion categories or affective appraisals (e.g., valence, arousal)? Is the recognition of emotion expressions discrete or continuous? Guided by a new theoretical approach to emotion taxonomies, we apply large-scale data collection and analysis techniques to judgments of 2,032 emotional vocal bursts produced in laboratory settings (Study 1) and 48 found in the real world (Study 2) by U.S. English speakers (N = 1,105). We find that vocal bursts convey at least 24 distinct kinds of emotion. Emotion categories (sympathy, awe), more so than affective appraisals (including valence and arousal), organize emotion recognition. In contrast to discrete emotion theories, the emotion categories conveyed by vocal bursts are bridged by smooth gradients with continuously varying meaning. We visualize the complex, high-dimensional space of emotion conveyed by brief human vocalization within an online interactive map.
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 ...of emotion recognition from speech prosody and nonlinguistic vocalizations, including expressers from 26 cultural groups and perceivers from 44 different cultures. Results showed that a wide variety of positive and negative emotions could be recognized with above-chance accuracy in cross-cultural conditions. However, there was also evidence for in-group advantage with higher accuracy in within- versus cross-cultural conditions. The distance between expresser and perceiver culture, measured via Hofstede’s cultural dimensions, was negatively correlated with recognition accuracy and positively correlated with in-group advantage. Results are discussed in relation to the dialect theory of emotion.
Central to emotion science is the degree to which categories, such as Awe, or broader affective features, such as Valence, underlie the recognition of emotional expression. To explore the processes ...by which people recognize emotion from prosody, US and Indian participants were asked to judge the emotion categories or affective features communicated by 2,519 speech samples produced by 100 actors from 5 cultures. With large-scale statistical inference methods, we find that prosody can communicate at least 12 distinct kinds of emotion that are preserved across the 2 cultures. Analyses of the semantic and acoustic structure of the recognition of emotions reveal that emotion categories drive the recognition of emotions more so than affective features, including Valence. In contrast to discrete emotion theories, however, emotion categories are bridged by gradients representing blends of emotions. Our findings, visualized within an interactive map, reveal a complex, high-dimensional space of emotional states recognized cross-culturally in speech prosody.
Work on voice sciences over recent decades has led to a proliferation of acoustic parameters that are used quite selectively and are not always extracted in a similar fashion. With many independent ...teams working in different research areas, shared standards become an essential safeguard to ensure compliance with state-of-the-art methods allowing appropriate comparison of results across studies and potential integration and combination of extraction and recognition systems. In this paper we propose a basic standard acoustic parameter set for various areas of automatic voice analysis, such as paralinguistic or clinical speech analysis. In contrast to a large brute-force parameter set, we present a minimalistic set of voice parameters here. These were selected based on a) their potential to index affective physiological changes in voice production, b) their proven value in former studies as well as their automatic extractability, and c) their theoretical significance. The set is intended to provide a common baseline for evaluation of future research and eliminate differences caused by varying parameter sets or even different implementations of the same parameters. Our implementation is publicly available with the openSMILE toolkit. Comparative evaluations of the proposed feature set and large baseline feature sets of INTERSPEECH challenges show a high performance of the proposed set in relation to its size.
Many authors have speculated about a close relationship between vocal expression of emotions and musical expression of emotions, but evidence bearing on this relationship has unfortunately been ...lacking. This review of 104 studies of vocal expression and 41 studies of music performance reveals similarities between the 2 channels concerning (a) the accuracy with which discrete emotions were communicated to listeners and (b) the emotion-specific patterns of acoustic cues used to communicate each emotion. The patterns are generally consistent with
K. R. Scherer's (1986)
theoretical predictions. The results can explain why music is perceived as expressive of emotion, and they are consistent with an evolutionary perspective on vocal expression of emotions. Discussion focuses on theoretical accounts and directions for future research.
This study extends previous work on emotion communication across cultures with a large-scale investigation of the physical expression cues in vocal tone. In doing so, it provides the first direct ...test of a key proposition of dialect theory, namely that greater accuracy of detecting emotions from one's own cultural group-known as in-group advantage-results from a match between culturally specific schemas in emotional expression style and culturally specific schemas in emotion recognition. Study 1 used stimuli from 100 professional actors from five English-speaking nations vocally conveying 11 emotional states (anger, contempt, fear, happiness, interest, lust, neutral, pride, relief, sadness, and shame) using standard-content sentences. Detailed acoustic analyses showed many similarities across groups, and yet also systematic group differences. This provides evidence for cultural accents in expressive style at the level of acoustic cues. In Study 2, listeners evaluated these expressions in a 5 × 5 design balanced across groups. Cross-cultural accuracy was greater than expected by chance. However, there was also in-group advantage, which varied across emotions. A lens model analysis of fundamental acoustic properties examined patterns in emotional expression and perception within and across groups. Acoustic cues were used relatively similarly across groups both to produce and judge emotions, and yet there were also subtle cultural differences. Speakers appear to have a culturally nuanced schema for enacting vocal tones via acoustic cues, and perceivers have a culturally nuanced schema in judging them. Consistent with dialect theory's prediction, in-group judgments showed a greater match between these schemas used for emotional expression and perception.
The current study investigated what can be understood from another person’s tone of voice. Participants from five English-speaking nations (Australia, India, Kenya, Singapore, and the United States) ...listened to vocal expressions of nine positive and nine negative affective states recorded by actors from their own nation. In response, they wrote open-ended judgments of what they believed the actor was trying to express. Responses cut across the chronological emotion process and included descriptions of situations, cognitive appraisals, feeling states, physiological arousal, expressive behaviors, emotion regulation, and attempts at social influence. Accuracy in terms of emotion categories was overall modest, whereas accuracy in terms of valence and arousal was more substantial. Coding participants’ 57,380 responses yielded a taxonomy of 56 categories, which included affective states as well as person descriptors, communication behaviors, and abnormal states. Open-ended responses thus reveal a wide range of ways in which people spontaneously perceive the intent behind emotional speech prosody.
We present a cross-cultural study on the performance and perception of affective expression in music. Professional bowed-string musicians from different musical traditions (Swedish folk music, ...Hindustani classical music, Japanese traditional music, and Western classical music) were instructed to perform short pieces of music to convey 11 emotions and related states to listeners. All musical stimuli were judged by Swedish, Indian, and Japanese participants in a balanced design, and a variety of acoustic and musical cues were extracted. Results first showed that the musicians' expressive intentions could be recognized with accuracy above chance both within and across musical cultures, but communication was, in general, more accurate for culturally familiar versus unfamiliar music, and for basic emotions versus nonbasic affective states. We further used a lens-model approach to describe the relations between the strategies that musicians use to convey various expressions and listeners' perceptions of the affective content of the music. Many acoustic and musical cues were similarly correlated with both the musicians' expressive intentions and the listeners' affective judgments across musical cultures, but the match between musicians' and listeners' uses of cues was better in within-cultural versus cross-cultural conditions. We conclude that affective expression in music may depend on a combination of universal and culture-specific factors.
Individuals vary in emotion recognition ability (ERA), but the causes and correlates of this variability are not well understood. Previous studies have largely focused on unimodal facial or vocal ...expressions and a small number of emotion categories, which may not reflect how emotions are expressed in everyday interactions. We investigated individual differences in ERA using a brief test containing dynamic multimodal (facial and vocal) expressions of 5 positive and 7 negative emotions (the ERAM test). Study 1 (N = 593) showed that ERA was positively correlated with emotional understanding, empathy, and openness, and negatively correlated with alexithymia. Women also had higher ERA than men. Study 2 was conducted online and replicated the recognition rates from Study 1 (which was conducted in lab) in a different sample (N = 106). Study 2 also showed that participants who had higher ERA were more accurate in their meta-cognitive judgments about their own accuracy. Recognition rates for visual, auditory, and audio-visual expressions were substantially correlated in both studies. Results provide further clues about the underlying structure of ERA and its links to broader affective processes. The ERAM test can be used for both lab and online research, and is freely available for academic research.
•The ERAM test assesses recognition of dynamic expressions of a wide range of emotions.•Includes items presented in video-only, audio-only, and audio-visual conditions.•Recognition of facial, vocal and multimodal expressions were substantially correlated.•ERAM scores correlated positively with emotion understanding, empathy, and openness.•Meta-cognitive judgments about accuracy were positively correlated with ERAM scores.
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