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. -Rainer Maria Rilke, "To Music" Communication of emotions is crucial to social relationships and survival (Ekman, 1992) . Many researchers argue that communication of emotions serves as the foundation of the social order in animals and humans (see Buck, 1984, pp. 31-36). However, such communication is also a significant feature of performing arts such as theater and music (G. D. Wilson, 1994, chap. 5). A convincing emotional expression is often desired, or even expected, from actors and musicians. The importance of such artistic expression should not be underestimated because there is now increasing evidence that how people express their emotions has implications for their physical health (e.g., Booth & Pennebaker, 2000; Buck, 1984, p. 229; Drummond & Quah, 2001; Giese-Davis & Spiegel, 2003; Siegman, Anderson, & Berger, 1990) . Two modalities that are often regarded as effective means of emotional communication are vocal expression (i.e., the nonverbal aspects of speech; Scherer, 1986) and music (Gabrielsson & Juslin, 2003) . Both are nonverbal channels that rely on acoustic signals for their transmission of messages. Therefore, it is not surprising that proposals about a close relationship between vocal expression and music have a long history (Helmholtz, 1863 (Helmholtz, /1954 Rousseau, 1761 Rousseau, /1986 Spencer, 1857) . In a classic article, "The Origin and Function of Music," Spencer (1857) argued that vocal music, and hence instrumental music, is intimately related to vocal expression of emotions. He ventured to explain the characteristics of both on physiological grounds, saying they are premised on "the general law that feeling is a stimulus to muscular action" (p. 400). In other words, he hypothesized that emotions influence physiological processes, which in turn influence the acoustic characteristics of both speech and singing. This notion, which we refer to as Spencer's law, formed the basis of most subsequent attempts to explain reported similarities between vocal expression and music (e.g., Fónagy & Magdics, 1963; Scherer, 1995; Sundberg, 1982) . Why should anyone care about such cross-modal similarities, if they really exist? First, the existence of acoustic similarities between vocal expression of emotions and music could help to explain why listeners perceive music as expressive of emotion (Kivy, 1980, p. 59). In this sense, an attempt to establish a link between the two domains could be made for the sake of theoretical economy, because principles from one domain (vocal expression) might help to explain another (music). Second, cross-modal similarities would support the common-although controversialhypothesis that speech and music evolved from a common origin (Brown, 2000; Levman, 2000; Scherer, 1995; Storr, 1992, chap. 1; Zucker, 1946) . A number of researchers have considered possible parallels between vocal expression and music (e.g., Fónagy & Magdics, 1963; Scherer, 1995; Sundberg, 1982) , but it is fair to say that previous work has been primarily speculative in nature. In fact, only recently have enough data from music studies accumulated to make possible a systematic comparison of the two domains. The purpose of this article is to review studies from both domains to determine whether the two modalities really communicate emotions in similar ways. The remainder of this article is organized as follows: First, we outline a theoretical perspective and a set of predictions. Second, we review parallels between vocal expression and music performance regarding (a) the accuracy with which Patrik N. Juslin and Petri Laukka, Department of Psychology, Uppsala University, Uppsala, Sweden. A brief summary of this review also appears in Juslin and Laukka (in press). The writing of this article was supported by the Bank of Sweden Tercentenary Foundation through Grant 2000-5193:02 to Patrik N. Juslin. We would like to thank Nancy Eisenberg and Klaus Scherer for useful comments on previous versions of this article. Correspondence concerning this article should be addressed to Patrik N. Juslin, Department of Psychology, Uppsala University, Box 1225, SE -751 42 Uppsala, Sweden. E-mail: patrik.juslin@psyk.uu.se Copyright 2003 by the American Psychological Association, Inc. 2003, Vol. 129, No. 5, 770 -814 0033-2909/03/$12.00 DOI: 10.1037DOI: 10. /0033-2909 770 different emotions are communicated to listeners and (b) the acoustic means used to communicate each emotion. Finally, we consider theoretical accounts and propose directions for future research. A review needs a perspective. In this overview, the perspective is provided by evolutionary psychology (Buss, 1995) . We argue that this approach offers the best account of the findings that we review, in particular if the theorizing is constrained by findings from neuropsychological and comparative studies (Panksepp & Panksepp, 2000) . In this section, we outline theory that serves to support the following seven guiding premises: (a) emotions may be regarded as adaptive reactions to certain prototypical, goalrelevant, and recurrent life problems that are common to many living organisms; (b) an important part of what makes emotions adaptive is that they are communicated nonverbally from one organism to another, thereby transmitting important information; (c) vocal expression is the most phylogenetically continuous of all forms of nonverbal communication; (d) vocal expressions of discrete emotions usually occur in similar types of life situations in different organisms; (e) the specific form that the vocal expressions of emotion take indirectly reflect these situations or, more specifically, the distinct physiological patterns that support the emotional behavior called forth by these situations; (f) physiological reactions influence an organism's voice production in differentiated ways; and (g) by imitating the acoustic characteristics of these patterns of vocal expression, music performers are able to communicate discrete emotions to listeners. The point of departure for an evolutionary perspective on emotional communication is that all human behavior depends on neurophysiological mechanisms. The only known causal process that is capable of yielding such mechanisms is evolution by natural selection. This is a feedback process that chooses among different mechanisms on the basis of how well they function; that is, function determines structure (Cosmides & Tooby, 2000, p. 95). Given that the mind acquired its organization through the evolutionary process, it may be useful to understand human functioning in terms of its adaptive significance (Cosmides & Tooby, 1994) . This is particularly true for such types of behavior that can be observed in other species as well (Bekoff, 2000; Panksepp, 1998) . Several researchers have taken an evolutionary approach to emotions. Before considering this literature, a preliminary definition of emotions is needed. Although emotions are difficult to define and measure (Plutchik, 1980) , most researchers would probably agree that emotions are relatively brief and intense reactions to goal-relevant changes in the environment that consist of many subcomponents: cognitive appraisal, subjective feeling, physiological arousal, expression, action tendency, and regulation (Scherer, 2000, p. 138). Thus, for example, an event may be appraised as harmful, evoking feelings of fear and physiological reactions in the body; individuals may express this fear verbally and nonverbally and may act in certain ways (e.g., running away) rather than others. However, researchers disagree as to whether emotions are best conceptualized as categories (Ekman, 1992) , dimensions (Russell, 1980) , prototypes (Shaver, Schwartz, Kirson, & O'Connor, 1987 ), or component processes (Scherer, 2001. In this review, we focus mainly on the expression component of emotion and adopt a categorical approach. According to the evolutionary approach, the key to understanding emotions is to study what functions emotions serve (Izard, 1993; Keltner & Gross, 1999) . Thus, to understand emotions one must consider how they reflect the environment in which they developed and to which they were adapted. On the basis of various kinds of evidence, Oatley and Jenkins (1996, chap. 3) suggested that humans' environment of evolutionary adaptedness about 200,000 years ago was that of seminomadic hunter-gatherer groups of 10 to 30 people living face-to-face with each other in extended families. Most emotions, they suggested, are presumably adapted to living this kind of way, which involved cooperating in activities such as hunting and rearing children. Several of the activities are associated with basic survival problems that most organisms have in common-avoiding predators, finding food, competing for resources, and caring for offspring. These problems, in turn, required specific types of adaptive reactions. A number of authors have suggested that such adaptive reactions were the prototypes of emotions as seen in humans (Plutchik, 1994, chap. 9; Scott, 1980) . This view of emotions is closely related to the concept of basic emotions, that is, the notion that there is a small number of discrete, innate, and universal emotion categories from which all other emotions may be derived (e.g., Ekman, 1992; Izard, 1992; Johnson-Laird & Oatley, 1992) . Each basic emotion can be defined, functionally, in terms of an appraisal of goal-relevant events that have recurred during evolution (see Power & Dalgleish, 1997, pp. 86 -99). Examples of such appraisals are given by Oatley (1992, p. 55): happiness (subgoals being achieved), anger (active plan frustrated), sadness (failure of major plan or loss of active goal), fear (self-preservation goal threatened or goal conflict), and disgust (gustatory goal violated). Basic emotions can be seen as fast and frugal algorithms (Gigerenzer & Goldstein, 1996) that deal with fundamental life issues under conditions of limited time, knowledge, or computational capacities. Having a small number of categories is an advantage in this context because it avoids the excessive information processing that comes with too many degrees of freedom (Johnson-Laird & Oatley, 1992) . The notion of basic emotions has been the subject of controversy (cf. Ekman, 1992; Izard, 1992; Ortony & Turner, 1990; Panksepp, 1992) . We propose that evidence of basic emotions may come from a range of sources that include findings of (a) distinct brain substrates associated with discrete emotions (Damasio et al., 2000; Panksepp, 1985 Phan, Wager, Taylor, & Liberzon, 2002) , (b) distinct patterns of physiological changes (Bloch, Orthous, & Santibañez, 1987; Ekman, Levenson, & Friesen, 1983; Fridlund, Schwartz, & Fowler, 1984; Levenson, 1992; Schwartz, Weinberger, & Singer, 1981) , (c) primacy of development of proposed basic emotions (Harris, 1989) , (d) crosscultural accuracy in facial and vocal expression of emotion (Elfenbein & Ambady, 2002) , (e) clusters that correspond to basic emotions in similarity ratings of affect terms (Shaver et al., 1987) , (f) reduced reaction times in lexical decision tasks when priming words are taken from the same basic emotion category (Conway & Bekerian, 1987) , and (g) phylogenetic continuity of basic emotions (Panksepp, 1998, chap. 1-3; Plutchik, 1980; Scott, 1980) . It is fair 771 COMMUNICATION OF EMOTIONS to acknowledge that some of these sources of evidence are not strong. In the case of autonomic specificity especially, the jury is still out (for a positive view, see Levenson, 1992 ; for a negative view, see Cacioppo, Berntson, Larsen, Poehlmann, & Ito, 2000) . 1 Arguably, the strongest evidence of basic emotions comes from studies of communication of emotions (Ekman, 1973 (Ekman, , 1992 . Evolutionary considerations may be especially relevant in the study of communication of emotions, because many researchers think that such communication serves important functions. First, expression of emotions allows individuals to communicate important information to others, which may affect their behaviors. Second, recognition of emotions allows individuals to make quick inferences about the probable intentions and behavior of others (Buck, 1984, chap. 2; Plutchik, 1994; chap. 10). The evolutionary approach implies a hierarchy in the ease with which various emotions are communicated nonverbally. Specifically, perceivers should be attuned to that information that is most relevant for adaptive action (e.g., Gibson, 1979) . It has been suggested that both expression and recognition of emotions proceed in terms of a small number of basic emotion categories that represent the optimal compromise between two opposing goals of the perceiver: (a) the desire to have the most informative categorization possible and (b) the desire to have these categories be as discriminable as possible (Juslin, 1998; cf. Ross & Spalding, 1994). To be useful as guides to action, emotions are recognized in terms of only a few categories related to life problems such as danger (fear), competition (anger), loss (sadness), cooperation (happiness) and caregiving (love). 2 By perceiving expressed emotions in terms of such basic emotion categories, individuals are able to make useful inferences in response to urgent events. It is arguable that the same selective pressures that shaped the development of the basic emotions should also favor the development of skills for expressing and recognizing the same emotions. In line with this reasoning, many researchers have suggested the existence of innate affect programs, which organize emotional expressions in terms of basic emotions (Buck, 1984; Clynes, 1977; Ekman, 1992; Izard, 1992; Lazarus, 1991; Tomkins, 1962) . Support for this notion comes from evidence of categorical perception of basic emotions in facial and vocal expression (de Gelder, Teunisse, & Benson, 1997; de Gelder & Vroomen, 1996; Etcoff & Magee, 1992 ; Laukka, in press), more or less intact vocal and facial expressions of emotion in children born deaf and blind (Eibl-Eibesfeldt, 1973) , and crosscultural accuracy in facial and vocal expression of emotion (Elfenbein & Ambady, 2002) . Phylogenetic continuity. Vocal expression may be the most phylogenetically continuous of all nonverbal channels. In his classic book, The Expression of the Emotions in Man and Animals, Darwin (1872/1998) reviewed different modalities of expression, including the voice: "With many kinds of animals, man included, the vocal organs are efficient in the highest degree as a means of expression" (p. 88). 3 Following Darwin's theory, a number of researchers of vocal expression have adopted an evolutionary perspective (H. Papoušek, Jürgens, & Papoušek, 1992) . A primary assumption is that there is phylogenetic continuity of vocal expression. Ploog (1992) described the morphological transformation of the larynx-from a pure respiratory organ (in lungfish) to a respiratory organ with a limited vocal capability (in amphibians, reptiles, and lower mammals) and, finally, to the sophisticated instrument that humans use to sing or speak in an emotionally expressive manner. Vocal expression seems especially important in social mammals. Social grouping evolved as a means of cooperative defense, although this implies that some kind of communication had to develop to allow sharing of tasks, space, and food (Plutchik, 1980) . Thus, vocal expression provided a means of social coordination and conflict resolution. MacLean (1993) has argued that the limbic system of the brain, an essential region for emotions, underwent an enlargement with mammals and that this development was related to increased sociality, as evident in play behavior, infant attachment, and vocal signaling. The degree of differentiation in the sound-producing apparatus is reflected in the organism's vocal behavior. For example, the primitive condition of the soundproducing apparatus in amphibians (e.g., frogs) permits only a few innate calls, such as mating calls, whereas the highly evolved larynx of nonhuman primates makes possible a rich repertoire of vocal expressions (Ploog, 1992) . The evolution of the phonatory apparatus toward its form in humans is paralleled not only by an increase in vocal repertoire but also by an increase in voluntary control over vocalization. It is possible to delineate three levels of development of vocal expression in terms of anatomic and phylogenetic development (e.g., Jürgens, 1992 Jürgens, , 2002 . The lowest level is represented by a completely genetically determined vocal reaction (e.g., pain shrieking). In this case, neither the motor pattern producing the vocal expression nor the eliciting stimulus has to be learned. This is referred to as an innate releasing mechanism. The brain structures responsible for the control of such mechanisms seem to be limited mainly to the brain stem (e.g., the periaqueductal gray). The following level of vocal expression involves voluntary control concerning the initiation and inhibition of the innate expressions. For example, rhesus monkeys may be trained in a vocal operant conditioning task to increase their vocalization rate if each 1 It seems to us that one argument is often overlooked in discussions regarding physiological specificity, namely that this may be a case in which positive results count as stronger evidence than do negative results. It is generally agreed that there are several methodological problems involved in measuring physiological indices (e.g., individual differences, timedependent nature of measures, difficulties in providing effective stimuli). Given the error variance, or "noise," that this produces, it is arguably more problematic for the no-specificity hypothesis that a number of studies have obtained similar and reliable emotion-specific patterns than it is for the specificity hypothesis that a number of studies have failed to yield such patterns. Failure to obtain patterns may be due to error variance, but how can the presence of similar patterns in several studies be explained? 2 Love is not included in most lists of basic emotions (e.g., Plutchik, 1994, p. 58), although some authors regard it as a basic emotion (e.g., Clynes, 1977; MacLean, 1993; Panksepp, 2000; Scott, 1980; Shaver et al., 1987) , as have philosophers such as Descartes, Spinoza, and Hobbes (Plutchik, 1994, p. 54). 3 In accordance with Spencer's law, Darwin (1872/1998) noted that vocalizations largely reflect physiological changes: "Involuntary . . . contractions of the muscles of the chest and the glottis . . . may first have given rise to the emission of vocal sounds. But the voice is now largely used for various purposes"; one purpose mentioned was "intercommunication" (p. 89). JUSLIN AND LAUKKA vocalization is rewarded with food (Ploog, 1992). Brain-lesioning studies of rhesus monkeys have revealed that this voluntary control depends on structures in the anterior cingulate cortex, and the same brain region has been implicated in humans (Jürgens & van Cramon, 1982). Neuroanatomical research has shown that the anterior cingulate cortex is directly connected to the periaqueductal region and thus in a position to exercise control over the more primitive vocalization center (Jürgens, 1992) . The highest level of vocal expression involves voluntary control over the precise acoustic patterns of vocal expression. This includes the capability to learn vocal patterns by imitation, as well as the production of new patterns by invention. These abilities are essential in the uniquely human inventions of language and music. Among the primates, only humans have gained direct cortical control over the voice, which is a prerequisite for singing. Neuroanatomical studies have indicated that nonhuman primates lack the direct connection between the primary motor cortex and the nucleus ambiguus (i.e., the site of the laryngeal motoneurons) that humans have (Jürgens, 1976; Kuypers, 1958) . Comparative research. Results from neurophysiological research that indicate that there is phylogenetic continuity of vocal expression have encouraged some researchers to embark on comparative studies of vocal expression. Although biologists and ethologists have tended to shy away from using words such as emotion in connection with animal behavior (Plutchik, 1994, chap. 10; Scherer, 1985) , a case could be made that most animal vocalizations involve motivational states that are closely related to emotions (Goodall, 1986; Hauser, 2000; Marler, 1977; Ploog, 1986; Richman, 1987; Scherer, 1985; Snowdon, 2003) . The states usually have to be inferred from the specific situations in which the vocalizations occurred. "In most of the circumstances in which animal signaling occurs, one detects urgent and demanding functions to be served, often involving emergencies for survival or procreation" (Marler, 1977, p. 54). There is little systematic work on vocal expression in animals, but several studies have indicated a close correspondence between the acoustic characteristics of animal vocalizations and specific affective situations (for reviews, see Plutchik, 1994, chap. 9 -10; Scherer, 1985; Snowdon, 2003) . For instance, Ploog (1981 Ploog ( , 1986 ) discovered a limited number of vocal expression categories in squirrel monkeys. These categories were related to important events in the monkeys' lives and included warning calls (alarm peeps), threat calls (groaning), desire for social contact calls (isolation peeps), and companionship calls (cackling). Given phylogenetic continuity of vocal expression and crossspecies similarity in the kinds of situations that generate vocal expression, it is interesting to ask whether there is any evidence of cross-species universality of vocal expression. Limited evidence of this kind has indeed been found (Scherer, 1985; Snowdon, 2003) . For instance, E. S. Morton (1977) noted that "birds and mammals use harsh, relatively low-frequency sounds when hostile, and higher-frequency, more pure tonelike sounds when frightened, appeasing, or approaching in a friendly manner" (p. 855; see also Ohala, 1983) . Another general principle, proposed by Jürgens (1979) , is that increasing aversiveness of primate vocal calls is correlated with pitch, total pitch range, and irregularity of pitch contours. These features have also been associated with negative emotion in human vocal expression (Davitz, 1964b; Scherer, 1986) . In animal studies, descriptions of vocal characteristics and emotional states are necessarily imprecise (Scherer, 1985) , making direct comparisons difficult. However, at the least these data suggest that there are some systematic relationships among acoustic measures and emotions. An important question is how such relationships and examples of crossspecies universality may be explained. According to Spencer's law, there should be common physiological principles. In fact, physiological variables determine to a large extent the nature of phonation and resonance in vocal expression (Scherer, 1989) , and there may be some reliable differentiation of physiological patterns for discrete emotions (Cacioppo et al., 2000, p. 180). It might be assumed that distinct physiological patterns reflect environmental demands on behavior: "Behaviors such as withdrawal, expulsion, fighting, fleeing, and nurturing each make different physiological demands. A most important function of emotion is to create the optimal physiological milieu to support the particular behavior that is called forth" (Levenson, 1994, p. 124). This process involves the central, somatic, and autonomic nervous systems. For example, fear is associated with a motivation to flee and brings about sympathetic arousal consistent with this action involving increased cardiovascular activation, greater oxygen exchange, and increased glucose availability (Mayne, 2001 ). Many physiological changes influence aspects of voice production, such as respiration, vocal fold vibration, and articulation, in welldifferentiated ways. For instance, anger yields increased tension in the laryngeal musculature coupled with increased subglottal air pressure. This changes the production of sound at the glottis and hence changes the timbre of the voice (Johnstone & Scherer, 2000) . In other words, depending on the specific physiological state, one may expect to find specific acoustic features in the voice. This general principle underlies Scherer's (1985) component process theory of emotion, which is the most promising attempt to formulate a stringent theory along the lines of Spencer's law. Using this theory, Scherer (1985) made detailed predictions about the patterns of acoustic cues (bits of information) associated with different emotions. The predictions were based on the idea that emotions involve sequential cognitive appraisals, or stimulus evaluation checks (SECs), of stimulus features such as novelty, intrinsic pleasantness, goal significance, coping potential, and norm or self compatibility (for further elaboration of appraisal dimensions, see Scherer, 2001 ). The outcome of each SEC is assumed to have a specific effect on the somatic nervous system, which in turn affects the musculature associated with voice production. In addition, each SEC outcome is assumed to affect various aspects of the autonomous nervous system (e.g., mucous and saliva production) in ways that strongly influence voice production. Scherer (1985) did not favor the basic emotions approach, although he offered predictions for acoustic cues associated with anger, disgust, fear, happiness, and sadness-"five major types of emotional states that can be expected to occur frequently in the daily life of many organisms, both animal and human" (p. 227). Later in this review, we provide a comparison of empirical findings from vocal expression and music performance with Scherer's (1986) revised predictions. Although human vocal expression of emotion is based on phylogenetically old parts of the brain that are in some respects similar to those of nonhuman primates, what is characteristic of humans is that they have much greater voluntary control over their vocaliza-773 COMMUNICATION OF EMOTIONS tion (Jürgens, 2002) . Therefore, an important distinction must be made between so-called push and pull effects in the determinants of vocal expression (Scherer, 1989) . Push effects involve various physiological processes, such as respiration and muscle tension, that are naturally influenced by emotional response. Pull effects, on the other hand, involve external conditions, such as social norms, that may lead to strategic posing of emotional expression for manipulative purposes (e.g., Krebs & Dawkins, 1984) . Vocal expression of emotions typically involves a combination of push and pull effects, and it is generally assumed that posed expression tends to be modeled on the basis of natural expression (Davitz, 1964c, p. 16; Owren & Bachorowski, 2001, p. 175; Scherer, 1985, p. 210). However, the precise extent to which posed expression is similar to natural expression is a question that requires further research. It is a recurrent notion that music is a means of emotional expression (Budd, 1985; S. Davies, 2001; Gabrielsson & Juslin, 2003) . Indeed, music has been defined as "one of the fine arts which is concerned with the combination of sounds with a view to beauty of form and the expression of emotion" (D. Watson, 1991, p. 8). It has been difficult to explain why music is expressive of emotions, but one possibility is that music is reminiscent of vocal expression of emotions. Previous perspectives. The notion that there is a close relationship between music and the human voice has a long history (Helmholtz, 1863 (Helmholtz, /1954 Kivy, 1980; Rousseau, 1761 Rousseau, /1986 Scherer, 1995; Spencer, 1857; Sundberg, 1982) . Helmholtz (1863/ 1954)-one of the pioneers of music psychology-noted that "an endeavor to imitate the involuntary modulations of the voice, and make its recitation richer and more expressive, may therefore possibly have led our ancestors to the discovery of the first means of musical expression" (p. 371). This impression is reinforced by the voicelike character of most musical instruments: "There are in the music of the violin . . . accents so closely akin to those of certain contralto voices that one has the illusion that a singer has taken her place amid the orchestra" (Marcel Proust, as cited in D. Watson, 1991, p. 236). Richard Wagner, the famous composer, noted that "the oldest, truest, most beautiful organ of music, the origin to which alone our music owes its being, is the human voice" (as cited in D. Watson, 1991, p. 2). Indeed, Stendhal commented that "no musical instrument is satisfactory except in so far as it approximates to the sound of the human voice" (as cited in D. Watson, 1991, p. 309). Many performers of blues music have been attracted to the vocal qualities of the slide guitar (Erlewine, Bogdanov, Woodstra, & Koda, 1996). Similarly, people often refer to the musical aspects of speech (e.g., Besson & Friederici, 1998; Fónagy & Magdics, 1963) , particularly in the context of infantdirected speech, where mothers use changes in duration, pitch, loudness, and timbre to regulate the infant's level of arousal (M. Papoušek, 1996) . The hypothesis that vocal expression and music share a number of expressive features might appear trivial in the light of all the arguments by different authors. However, these comments are primarily anecdotal or speculative in nature. Indeed, many authors have disputed this hypothesis. S. Davies (2001) observed that it has been suggested that expressive instrumental music recalls the tones and intonations with which emotions are given vocal expression (Kivy, 1989), but this . . . is dubious. It is true that blues guitar and jazz saxophone sometimes imitate singing styles, and that singing styles sometimes recall the sobs, wails, whoops, and yells that go with ordinary occasions of expressiveness. For the general run of cases, though, music does not sound very like the noises made by people gripped by emotion. (p. 31) (See also Budd, 1985, p. 148; Levman, 2000, p. 194.) Thus, awaiting relevant data, it has been uncertain whether Spencer's law can provide an account of music's expressiveness. Boundary conditions of Spencer's law. It does actually seem unlikely that Spencer's law can explain all of music's expressiveness. For instance, there are several aspects of musical form (e.g., harmonic progression) that have no counterpart in vocal expression but that nonetheless contribute to music's expressiveness (e.g., Gabrielsson & Juslin, 2003) . Consequently, Spencer's law cannot be the whole story of music's expressiveness. In fact, there are many sources of emotion in relation to music (e.g., ) including musical expectancy (Meyer, 1956 ), arbitrary association (J. B. Davies, 1978) , and iconic significationthat is, structural similarity between musical and extramusical features (Langer, 1951) . Only the last of these sources corresponds to Spencer's law. Yet, we argue that Spencer's law should be part of any satisfactory account of music's expressiveness. For the hypothesis to have explanatory power, however, it must be constrained. What is required, we propose, is specification of the boundary conditions of the hypothesis. We argue that the hypothesis that there is an iconic similarity between vocal expression of emotion and musical expression of emotion applies only to certain acoustic features-primarily those features of the music that the performer can control (more or less freely) during his or her performance such as tempo, loudness, and timbre. However, the hypothesis does not apply to such features of a piece of music that are usually indicated in the notation of the piece (e.g., harmony, tonality, melodic progression), because these features reflect to a larger extent characteristics of music as a human art form that follows its own intrinsic rules and that varies from one culture to another (Carterette & Kendall, 1999; Juslin, 1997c) . Neuropsychological research indicates that certain aspects of music (e.g., timbre) share the same neural resources as speech, whereas others (e.g., tonality) draw on resources that are unique to music (Patel & Peretz, 1997; see also Peretz, 2002). Thus, we argue that musicians communicate emotions to listeners via their performances of music by using emotion-specific patterns of acoustic cues derived from vocal expression of emotion (Juslin, 1998) . The extent to which Spencer's law can offer an explanation of music's expressiveness is directly proportional to the relative contribution of performance variables to the listener's perception of emotions in music. Because performance variables include such perceptually salient features as speed and loudness, this contribution is likely to be large. It is well-known that the same sentence may be pronounced in a large number of different ways, and that the way in which it is pronounced may convey the speaker's state of emotion. In principle, one can separate the verbal message from its acoustic realization in speech. Similarly, the same piece of music can be played in a number of different ways, and the way in which it is played may convey specific emotions to listeners. In principle, one can sepa-774 JUSLIN AND LAUKKA rate the structure of the piece, as notated, from its acoustic realization in performance. Therefore, to obtain possible similarities, how speakers and musicians express emotions through the ways in which they convey verbal and musical contents should be explored (i.e., "It's not what you say, it's how you say it"). The origins of the relationship. If musical expression of emotion should turn out to resemble vocal expression of emotion, how did musical expression come to resemble vocal expression in the first place? The origins of music are, unfortunately, forever lost in the history of our ancestors (but for a survey of theories, see various contributions in Wallin, Merker, & Brown, 2000). However, it is apparent that music accompanies many important human activities, and this is especially true of so-called preliterate cultures (e.g., Becker, 2001; Gregory, 1997) . It is possible to speculate that the origin of music is to be found in various cultural activities of the distant past, when the demarcation between vocal expression and music was not as clear as it is today. Vocal expression of discrete emotions such as happiness, sadness, anger, and love probably became gradually meshed with vocal music that accompanied related cultural activities such as festivities, funerals, wars, and caregiving. A number of authors have proposed that music served to harmonize the emotions of the social group and to create cohesion: "Singing and dancing serves to draw groups together, direct the emotions of the people, and prepare them for joint action" (E. O. Wilson, 1975, p. 564). There is evidence that listeners can accurately categorize songs of different emotional types (e.g., festive, mourning, war, lullabies) that come from different cultures (Eggebrecht, 1983) and that there are similarities in certain acoustic characteristics used in such songs; for instance, mourning songs typically have slow tempo, low sound level, and soft timbre, whereas festive songs have fast tempo, high sound level, and bright timbre (Eibl-Eibesfeldt, 1989, p. 695). Thus, it is reasonable to hypothesize that music developed from a means of emotion sharing and communication to an art form in its own right (e.g., Juslin, 2001b; Levman, 2000, p. 203; Storr, 1992, p. 23; Zucker, 1946, p. 85). In the foregoing, we outlined an evolutionary perspective according to which music performers are able to communicate basic emotions to listeners by using a nonverbal code that derives from vocal expression of emotion. We hypothesized that vocal expression is an evolved mechanism based on innate, fairly stable, and universal affect programs that develop early and are fine-tuned by prenatal experiences (Mastropieri & Turkewitz, 1999; Verny & Kelly, 1981) . We made the following five predictions on the basis of this evolutionary approach. First, we predicted that communication of basic emotions would be accurate in both vocal and musical expression. Second, we predicted that there would be cross-cultural accuracy of communication of basic emotions in both channels, as long as certain acoustic features are involved (speed, loudness, timbre). Third, we predicted that the ability to recognize basic emotions in vocal and musical expression develops early in life. Fourth, we predicted that the same patterns of acoustic cues are used to communicate basic emotions in both channels. Finally, we predicted that the patterns of cues would be consistent with Scherer's (1986) physiologically based predictions. These five predictions are addressed in the following empirical review. Definitions and Method of the Review Vocal expression and music performance arguably belong to the general class of nonverbal communication behavior. Fundamental issues concerning nonverbal communication include (a) the content (What is communicated?), (b) the accuracy (How well is it communicated?), and (c) the code usage (How is it communicated?). Before addressing these questions, one should first make sure that communication has occurred. Communication implies (a) a socially shared code, (b) an encoder who intends to express something particular via that code, and (c) a decoder who responds systematically to that code (e.g., Shannon & Weaver, 1949; Wiener, Devoe, Rubinow, & Geller, 1972) . True communication has taken place only if the encoder's expressive intention has become mutually known to the encoder and the decoder (e.g., Ekman & Friesen, 1969) . We do not exclude that information may be unwittingly transmitted from one person to another, but this would not count as communication according to the present definition (for a different view, see Buck, 1984, pp. 4 -5). An important aspect of the communicative process is the coding of the nonverbal signs (the manner in which information is transmitted through the signal). According to Ekman and Friesen (1969) , the nature of the coding can be described by three dimensions: discrete versus continuous, probabilistic versus invariant, and iconic versus arbitrary. Nonverbal signals are typically coded continuously, probabilistically, and iconically. To illustrate, (a) the loudness of the voice changes continuously (rather than discretely); (b) increases in loudness frequently (but not always) signify anger; and (c) the loudness is iconically (rather than arbitrarily) related to the intensity of the felt anger (e.g., the loudness increases when the felt intensity of the anger increases; Juslin & Laukka, 2001, Figure 4 ). Studies of vocal expression and studies of music performance have typically been carried out separately from each other. However, one could argue that the two domains share a number of important characteristics. First, both domains are concerned with a channel that uses patterns of pitch, loudness, and duration to communicate emotions (the content). Second, both domains have investigated the same questions (How accurate is the communication?, What is the nature of the code?). Third, both domains have used similar methods (decoding experiments, acoustic analyses). Hence, both domains have confronted many of the same problems (see the Discussion section). In a typical study of communication of emotions in vocal expression or music performance, the encoder (speaker/performer in vocal expression/ music performance, respectively) is presented with material to be spoken/ performed. The material usually consists of brief sentences or melodies. Each sentence/melody is to be spoken/performed while expressing different emotions prechosen by the experimenter. The emotion portrayals are recorded and used in listening tests to study whether listeners can decode the expressed emotions. Each portrayal is analyzed to see what acoustic cues are used in the communicative process. The assumption is that, because the verbal/musical material remains the same in different portrayals, whatever effects that appear in listeners' judgments or acoustic measures should primarily be the result of the encoder's expressive intention. This procedure, often referred to as the standard content paradigm (Davitz, 1964b) , is not without its problems, but we temporarily postpone our critique until the Discussion section. COMMUNICATION OF EMOTIONS We used two criteria for inclusion of studies in the present review. First, we included only studies focusing on nonverbal aspects of speech or performance-related aspects of music. This is in accordance with the boundary conditions of the hypothesis discussed above. Second, we included only studies that investigated the communication of discrete emotions (e.g., sadness). Hence, studies that focused on emotional arousal in general (e.g., Murray, Baber, & South, 1996) or on emotion dimensions (e.g., Laukka, Juslin, & Bresin, 2003) were not included in the review. Similarly, studies that used the standard paradigm but that did not use explicitly defined emotions (e.g., Cosmides, 1983) or that used only positive versus negative affect (e.g., Fulcher, 1991) were not included. Such studies do not allow for the relevant comparisons with studies of music performance, which have almost exclusively studied discrete emotions. Emotion in vocal expression and music performance is a multidisciplinary field of research. The majority of studies have been conducted by psychologists, but contributions also come from, for instance, acoustics, speech science, linguistics, medicine, engineering, computer science, and musicology. Publications are scattered among so many sources that even many review articles have not surveyed more than a subset of the literature. To ensure that this review was as complete as possible, we searched for relevant investigations by using a variety of sources. More specifically, the studies included in the present review were gathered using the following Internet-based scientific databases: PsycINFO, MEDLINE, Linguistics and Language Behavior, Ingenta, and RILM Abstracts of Music Literature. Whenever possible, the year limits were set at articles published since 1900. The following words, in various combinations and truncations, were used in the literature search : emotion, affective, vocal, voice, speech, prosody, paralanguage, music, music performance, and expression. The goal was to include all English language publications in peer-reviewed journals. We have also included additional studies located via informal sources, including studies reported in conference proceedings, in other languages, and in unpublished doctoral dissertations that we were able to locate. It should be noted that the majority of studies in both domains correspond to the selection criteria above. We located 104 studies of vocal expression and 41 studies of music performance in our literature search, which was completed in June 2002. We review the findings in terms of five general categories of emotion: anger, fear, happiness, sadness, and love-tenderness, primarily because these are the only five emotion categories for which there is enough evidence in both vocal expression and music performance. They roughly correspond to the basic emotions described earlier. 4 These five categories represent a reasonable point of departure because all of them comprise what are regarded as typical emotions by lay people (Shaver et al., 1987; Shields, 1984) . There is also evidence that these emotions closely correspond to the first emotion terms children learn to use (e.g., Camras & Allison, 1985) and that they serve as basic-level categories in cognitive representations of emotions (e.g., Shaver et al., 1987) . Their role in musical expression of emotions is highlighted by questionnaire research (Lindström, Juslin, Bresin, & Williamon, 2003) in which 135 music students were asked what emotions can be expressed in music. Happiness, sadness, fear, love, and anger were among the 10 most highly rated words of a list of 38 words containing both basic and complex emotions. An important question concerns the exact words used to denote the emotions. A number of different words have been used in the literature, and there is little agreement so far regarding the organization of the emotion lexicon (Plutchik, 1994, p. 45). Therefore, it is not clear how words such as happiness and joy should be distinguished. The most prudent approach to take is to treat different but closely related emotion words (e.g., sorrow, grief, sadness) as belonging to the same emotion family (e.g., the sadness family; Ekman, 1992). Table 1 shows how the emotion words used in the present studies have been categorized in this review (for some empirical support, see the analyses of emotion words presented by Johnson-Laird & Oatley, 1989; Shaver at al., 1987) . Darwin (1872/1998) discussed both vocal and facial expression of emotions in his treatise. In recent years, however, facial expression has received far more empirical research than vocal expression. There are a number of reasons for this, such as the problems associated with the recording and analysis of speech sounds (Scherer, 1982) . The consequence is that the code used in facial expression of emotion is better understood than the code used in vocal expression. This is unfortunate, however, because recent studies using self-reports have revealed that, if anything, 4 Most theorists distinguish between passionate love (eroticism) and companionate love (tenderness; Hatfield & Rapson, 2000, p. 660), of which the latter corresponds to our love-tenderness category. Some researchers suggest that all kinds of love originally derived from this emotional state, which is associated with infant-caregiver attachment (e.g., Eibl-Eibesfeldt, 1989, chap. 4; Oatley & Jenkins, 1996; p. 287; Panksepp, 1998, chap. 13 Table 2 provides a summary of 104 studies of vocal expression included in this review in terms of authors, publication year, emotions studied, method used (e.g., portrayal, manipulated portrayal, induction, natural speech sample, synthesis), language, acoustic cues analyzed (where applicable), and verbal material. Thirty-nine studies presented data that permitted us to include them in a meta-analysis of communication accuracy (detailed below). The majority of studies (58%) used English-speaking encoders, although as many as 18 different languages, plus nonsense utterances, are represented in the studies reviewed. Twelve studies (12%) can be characterized as more or less cross-cultural in that they included analyses of encoders or decoders from more than one nation. The verbal material features series of numbers, letters of the alphabet, nonsense syllables, or regular speech material (e.g., words, sentences, paragraphs). The number of emotions included ranges from 1 to 15 (M ϭ 5.89). Ninety studies (87%) used emotion portrayals by actors, 13 studies (13%) used manipulations of portrayals (e.g., filtering, masking, reversal), 7 studies (7%) used mood induction procedures, and 12 studies (12%) used natural speech samples. The latter comes mainly from studies of fear expressions in aviation accidents. Twenty-one studies (20%) used sound synthesis, or copy synthesis. 5 Seventy-seven studies (74%) reported acoustic data, of which 6 studies used listeners' ratings of cues rather than acoustic measurements. Studies of music performance have been conducted for more than 100 years (for reviews, see Gabrielsson, 1999; Palmer, 1997) . However, these studies have almost exclusively focused on structural aspects of performance such as marking of the phrase structure, whereas emotion has been ignored. Those studies that have been concerned with emotion in music, on the other hand, have almost exclusively focused on expressive aspects of musical composition such as pitch or mode (e.g., Gabrielsson & Juslin, 2003) , whereas they have ignored aspects of specific performances. That performance aspects of emotional expression did not gain attention much earlier is strange considering that one of the great pioneers in music psychology, Carl E. Seashore, made detailed proposals about such studies in the 1920s (Seashore, 1927) . Seashore (1947) later suggested that music researchers could use the same paradigm that had been used in vocal expression (i.e., the standard content paradigm) to investigate how performers express emotions. However, Seashore's (1947) plea went unheard, and he did not publish any study of that kind himself. After slow initial progress, there was an increase of studies in the 1990s (23 studies published). This seems to continue into the 2000s (10 studies published 2000 -2002). The increase is perhaps a result of the increased availability of software for digital analysis of acoustic cues, but it may also reflect a renaissance for research on musical emotion . Figure 1 illustrates the timeliness of this review in terms of the studies available for a comparison of the two domains. Table 3 provides a summary of the 41 studies of emotional expression in music performance included in the review in terms of authors, publication year, emotions studied, method used (e.g., portrayal, manipulated portrayal, synthesis), instrument used, number and nationality of performers and listeners, acoustic cues analyzed (where applicable), and musical material. Twelve studies (29%) provided data that permitted us to include them in a meta-analysis of communication accuracy. These studies covered a wide range of musical styles, including classical music, folk music, Indian ragas, jazz, pop, rock, children's songs, and free improvisations. The most common musical style was classical music (17 studies, 41%). Most studies relied on the standard paradigm used in studies of vocal expression of emotions. The number of emotions studied ranges from 3 to 9 (M ϭ 4.98), and emotions typically included happiness, sadness, anger, fear, and tenderness. Twelve musical instruments were included. The most frequently studied instrument was singing voice (19 studies), followed by guitar (7), piano (6), synthesizer (4), violin (3), flute (2), saxophone (2), drums (1), sitar (1), timpani (1), trumpet (1), xylophone (1), and sentograph (1-a sentograph is an electronic device for recording patterns of finger pressure over time-see Clynes, 1977) . At least 12 different nationalities are represented in the studies (Fónagy & Magdics, 1963 , did not state the nationalities clearly), with Sweden being most strongly represented (39%), followed by Japan (12%) and the United States (12%). Most of the studies analyzed professional musicians (but see Juslin & Laukka, 2000) , and the performances were usually monophonic to facilitate measurement of acoustic parameters (for an exception, see Dry & Gabrielsson, 1997) . (Monophonic melody is probably one of the earliest forms of music, Wolfe, 2002.) A few studies (15%) investigated what means listeners use to decode emotions by means of synthesized performances. Eighty-five percent of the studies reported data on acoustic cues; of these studies, 5 used listeners' ratings of cues rather than acoustic measurements. Results Studies of vocal expression and music performance have converged on the conclusion that encoders can communicate basic emotions to decoders with above-chance accuracy, at least for the five emotion categories considered here. To examine these data closer, we conducted a meta-analysis of decoding accuracy. Included in this analysis were all studies that presented (or allowed computation of) forced-choice decoding data relative to some independent criterion of encoding intention. Thirty-nine studies of vocal expression and 12 studies of music performance met this criterion, featuring a total of 73 decoding experiments, 60 for vocal expression, 13 for music performance. One problem in comparing accuracy scores from different studies is that they use different numbers of response alternatives in the decoding task. Rosenthal and Rubin's (1989) effect size index for one-sample, multiple-choice-type data, pi (), allows researchers to transform accuracy scores involving any number of response alternatives to a standard scale of dichotomous choice, on which .50 is the null value and 1.00 corresponds to 100% correct decoding. Ideally, an index of decoding accuracy should also take into account the response bias in the decoder's judgments (Wagner, 1993) . However, this requires that results be presented in terms of a confusion matrix, which very few studies have done. Therefore, we summarize the data simply in terms of Rosenthal and Rubin's pi index. Summary statistics. Table 4 summarizes the main findings from the meta-analysis in terms of summary statistics (i.e., unweighted mean, weighted mean, median, standard deviation, (text continues on page 786) 5 Copy synthesis refers to copying acoustic features from real emotion portrayals and using them to resynthesize new portrayals. This method makes it possible to manipulate certain cues of an emotion portrayal while leaving other cues intact (e.g., Juslin & Madison, 1999; Ladd et al., 1985; Schröder, 2001  Brief sentence, vowels 95. Tischer (199395. Tischer ( , 1995
REF conducted a comprehensive review of vocal expressions and music performance, finding substantial overlap in the cues used to convey basic emotions in speech and music.
Communication of emotions in vocal expression and music performance: Different channels, same code?
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