Patrik N. Juslin

Communication of emotions in vocal expression and music performance : Different channels, same code?

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. Scherers (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.

Expression, perception, and induction of musical emotions : A review and a questionnaire study of everyday listening

In this article, we provide an up-to-date overview of theory and research concerning expression, perception, and induction of emotion in music. We also provide a critique of this research, noting that previous studies have tended to neglect the social context of music listening. The most likely reason for this neglect, we argue, is that that most research on musical emotion has, implicitly or explicitly, taken the perspective of the musician in understanding responses to music. In contrast, we argue that a promising avenue toward a better understanding of emotional responses to music involves diary and questionnaire studies of how ordinary listeners actually use music in everyday life contexts. Accordingly, we present findings from an exploratory questionnaire study featuring 141 music listeners (between 17 and 74 years of age) that offers some novel insights. The results provide preliminary estimates of the occurrence of various emotions in listening to music, as well as clues to how music is used by listeners in a number of different emotional ways in various life contexts. These results confirm that emotion is strongly related to most peoples primary motives for listening to music.

Emotional Expression in Music Performance: Between the Performer's Intention and the Listener's Experience

Nine professional musicians were instructed to perform short melodies using various instruments - the violin, electric guitar, flute, and singing voice - so as to communicate specific emotional characters to listeners. The performances were first validated by having listeners rating the emotional expression and then analysed with regard to their physical characteristics, e.g. tempo, dynamics, timing, and spectrum. The main findings were that (a) the performers expressive intention had a marked effect on all analysed variables; (b) the performers showed many similarities as well as individual differences in emotion encoding; (c) listeners were generally successful in decoding the intended expression; and (d) some emotional characters seemed easier to communicate than others. The reported results imply that we are unlikely to find performance rules independent of instrument, musical style, performer, or listener.

Handbook of music and emotion: Theory, research, applications

PART I: OVERTURE PART II: MULTIDISCIPLINARY PERSPECTIVES PART III: MEASUREMENT PART IV: MUSIC MAKING PART V: MUSIC LISTENING PART VI: DEVELOPMENT, PERSONALITY AND SOCIAL FACTORS PART VII: APPLICATIONS PART VIII: ENCORE

Emotional responses to music: experience, expression, and physiology

A crucial issue in research on music and emotion is whether music evokes genuine emotional responses in listeners (the emotivist position) or whether listeners merely perceive emotions expressed by the music (the cognitivist position). To investigate this issue, we measured self-reported emotion, facial muscle activity, and autonomic activity in 32 participants while they listened to popular music composed with either a happy or a sad emotional expression. Results revealed a coherent manifestation in the experiential, expressive, and physiological components of the emotional response system, which supports the emotivist position. Happy music generated more zygomatic facial muscle activity, greater skin conductance, lower finger temperature, more happiness and less sadness than sad music. The finding that the emotion induced in the listener was the same as the emotion expressed in the music is consistent with the notion that music may induce emotions through a process of emotional contagion.

An experience sampling study of emotional reactions to music: listener, music, and situation

The Experience Sampling Method was used to explore emotions to music as they naturally occurred in everyday life, with a focus on the prevalence of different musical emotions and how such emotions are related to various factors in the listener, the music, and the situation. Thirty-two college students, 20 to 31 years old, carried a palmtop that emitted a sound signal seven times per day at random intervals for 2 weeks. When signaled, participants were required to complete a questionnaire on the palmtop. Results showed that music occurred in 37% of the episodes, and in 64% of the music episodes, the participants reported that the music affected how they felt. Comparisons showed that happiness-elation and nostalgia-longing were more frequent in episodes with musical emotions, whereas anger-irritation, boredom-indifference, and anxiety-fear were more frequent in episodes with nonmusical emotions. The prevalence of specific musical emotions correlated with personality measures and also varied depending on the situation (e.g., current activity, other people present), thus highlighting the need to use representative samples of situations to obtain valid estimates of prevalence.

Five Facets of Musical Expression: A Psychologist's Perspective on Music Performance

The aim of this article is to outline a psychological approach to expression in music performance that could help to provide a solid foundation for the teaching of expressive skills in music education. Drawing on previous research, the author suggests that performance expression is best conceptualized as a multi-dimensional phenomenon consisting of five primary components: (a) Generative rules that function to clarify the musical structure; (b) Emotional expression that serves to convey intended emotions to listeners; (c) Random variations that reflect human limitations with regard to internal time-keeper variance and motor delays; (d) Motion principles that prescribe that some aspects of the performance (e.g. timing) should be shaped in accordance with patterns of biological motion; and (e) Stylistic unexpectedness that involves local deviations from performance conventions. An analysis of performance expression in terms of these five components - collectively referred to as the GERMS model - has important implications for research and teaching of music performance.

Music and emotion

The question of the precise link between music and emotions has exercised scholars since the time of ancient Greece. The goal of this chapter is to review contemporary empirical research on music and emotion primarily within music psychology. We begin by commenting on the recent history of the field. Then, we provide a working definition of emotions. The main part of the chapter is devoted to a systematic overview of empirical studies, first on perception of emotions, and second on arousal of emotions. We then review two specific themes in current research—development and neuroscience—and offer an outlook on the future. We conclude that music-emotion research has solid achievements on which to build, but that the field is in the need of studies with a more theoretical and applicable orientation.

Toward a Computational Model of Expression in Music Performance: The GERM Model

This article presents a computational model of expression in music performance: the GERM model. The purpose of the GERM model is to (a) describe the principal sources of variability in music performance, (b) emphasize the need to integrate different aspects of performance in a common model, and (c) provide some preliminaries (germ = a basis from which a thing may develop) for a computational model that simulates the different aspects. Drawing on previous research on performance, we propose that performance expression derives from four main sources of variability: (1) Generative Rules, which function to convey the generative structure in a musical manner (e.g., Clarke, 1988; Sundberg, 1988); (2) Emotional Expression, which is governed by the performers expressive intention (e.g., Juslin, 1997a); (3) Random Variations, which reflect internal timekeeper variance and motor delay variance (e.g., Gilden, 2001; Wing and Kristofferson, 1973); and (4) Movement Principles, which prescribe that certain features of the performance are shaped in accordance with biological motion (e.g., Shove and Repp, 1995). A preliminary version of the GERM model was implemented by means of computer synthesis. Synthesized performances were evaluated by musically trained participants in a listening test. The results from the test support a decomposition of expression in terms of the GERM model. Implications for future research on music performance are discussed.

Emotional reactions to music in a nationally representative sample of Swedish adults: Prevalence and causal influences

Empirical studies have indicated that listeners value music primarily for its ability to arouse emotions. Yet little is known about which emotions listeners normally experience when listening to music, or about the causes of these emotions. The goal of this study was therefore to explore the prevalence of emotional reactions to music in everyday life and how this is influenced by various factors in the listener, the music, and the situation. A self-administered mail questionnaire was sent to a random and nationally representative sample of 1,500 Swedish citizens between the ages of 18 and 65, and 762 participants (51%) responded to the questionnaire. Thirty-two items explored both musical emotions in general (semantic estimates) and the most recent emotion episode featuring music for each participant (episodic estimates). The results revealed several variables (e.g., personality, age, gender, listener activity) that were correlated with particular emotions. A multiple discriminant analysis indicated that three of the most common emotion categories in a set of musical episodes (i.e., happiness, sadness, nostalgia) could be predicted with a mean accuracy of 70% correct based on data obtained from the questionnaire. The results may inform theorizing about musical emotions and guide the selection of causal variables for manipulation in future experiments.