The field of sonification has progressed greatly over the past twenty years and currently constitutes an established area of research. This article aims at exploiting and organizing the knowledge accumulated in previous experimental studies to build a foundation for future sonification works. A systematic review of these studies may reveal trends in sonification design, and therefore support the development of design guidelines. To this end, we have reviewed and analyzed 179 scientific publications related to sonification of physical quantities. Using a bottom-up approach, we set up a list of conceptual dimensions belonging to both physical and auditory domains. Mappings used in the reviewed works were identified, forming a database of 495 entries. Frequency of use was analyzed among these conceptual dimensions as well as higher-level categories. Results confirm two hypotheses formulated in a preliminary study: pitch is by far the most used auditory dimension in sonification applications, and spatial auditory dimensions are almost exclusively used to sonify kinematic quantities. To detect successful as well as unsuccessful sonification strategies, assessment of mapping efficiency conducted in the reviewed works was considered. Results show that a proper evaluation of sonification mappings is performed only in a marginal proportion of publications. Additional aspects of the publication database were investigated: historical distribution of sonification works is presented, projects are classified according to their primary function, and the sonic material used in the auditory display is discussed. Finally, a mapping-based approach for characterizing sonification is proposed.

This study explored a dimensional approach to vocal expression of emotion. Actors vocally portrayed emotions (anger, disgust, fear, happiness, sadness) with weak and strong emotion intensity. Listeners (30 university students and 6 speech experts) rated each portrayal on four emotion dimensions (activation, valence, potency, emotion intensity). The portrayals were also acoustically analysed with respect to 20 vocal cues (e.g., speech rate, voice intensity, fundamental frequency, spectral energy distribution). The results showed that: (a) there were distinct patterns of ratings of activation, valence, and potency for the different emotions; (b) all four emotion dimensions were correlated with several vocal cues; (c) listeners' ratings could be successfully predicted from the vocal cues for all dimensions except valence; and (d) the intensity dimension was positively correlated with the activation dimension in the listeners' ratings.

Much has been written about expressivity by philosophers, composers, musicologists, and psychologists, but little is known about how the musicians of tomorrow — music students — approach this subject. This paper reports an exploratory study in which 135 students from music conservatories in three countries (England, Italy, Sweden) filled out a questionnaire that addressed four themes: (a) conceptualizing expressivity, (b) expressivity in everyday practice, (c) expressivity in music teaching, and (d) novel teaching strategies. The results suggest that students define expressivity mainly in terms of communicating emotions and `playing with feeling'. Expressive skills are regarded as highly important by students, and they would like to practice more on expressivity than is currently the case. However, most students are skeptical toward using computers in teaching of expressivity since they cannot see how such applications could work. The results suggest that expressivity deserves more attention in music education than has hitherto been the case.

The aim of this study is to manipulate musical cues systematically to determine the aspects of music that contribute to emotional expression, and whether these cues operate in additive or interactive fashion, and whether the cue levels can be characterized as linear or non-linear. An optimized factorial design was used with six primary musical cues (mode, tempo, dynamics, articulation, timbre, and register) across four different music examples. Listeners rated 200 musical examples according to four perceived emotional characters (happy, sad, peaceful, and scary). The results exhibited robust effects for all cues and the ranked importance of these was established by multiple regression. The most important cue was mode followed by tempo, register, dynamics, articulation, and timbre, although the ranking varied across the emotions. The second main result suggested that most cue levels contributed to the emotions in a linear fashion, explaining 77–89% of variance in ratings. Quadratic encoding of cues did lead to minor but significant increases of the models (0–8%). Finally, the interactions between the cues were non-existent suggesting that the cues operate mostly in an additive fashion, corroborating recent findings on emotional expression in music (Juslin and Lindström, 2010).