Expressive Music Performance Research Articles

Teaching young musicians expressive performance: an experimental study

ABSTRACTTwenty-nine pupils (aged 8–15) took part in an improvisation test and an experimental vs. control group teaching session. The aim of the improvisation test was to explore whether participants had knowledge about the use of expressive cues to convey basic emotions in improvisations. Assessments of the improvisations by four adjudicators indicated that most pupils in this sample could convey happiness, sadness and anger effectively in improvisations, providing a useful starting point for expressive music performance, which was examined in the experimental study. The experimental study investigated whether discussion of musical character is effective for improving pupils’ expressiveness, by comparing outcomes with a control teaching session that focused on accuracy and technical fluency. Participants’ performances of a ‘happy’ and ‘sad’ musical excerpt pre- and post-teaching were assessed by four adjudicators. Results indicated that the experimental teaching had been significantly more effective for improving expressiveness in the ‘sad’ extract than control teaching.

Notating disfluencies and temporal deviations in music and arrhythmia

Expressive music performance and cardiac arrhythmia can be viewed as deformations of, or deviations from, an underlying pulse stream. I propose that the results of these pulse displacements can be treated as actual rhythms and represented accurately via a literal application of common music notation, which encodes proportional relations among duration categories, and figural and metric groupings. I apply the theory to recorded music containing extreme timing deviations and to electrocardiographic (ECG) recordings of cardiac arrhythmias. The rhythm transcriptions are based on rigorous computer-assisted quantitative measurements of onset timings and durations. The root-mean-square error ranges for the rhythm transcriptions were (19.1, 87.4) ms for the music samples and (24.8, 53.0) ms for the arrhythmia examples. For the performed music, the representation makes concrete the gap between the score and performance. For the arrhythmia ECGs, the transcriptions show rhythmic patterns evolving through time, progressions which are obscured by predominant individual beat morphology- and frequency-based representations. To make tangible the similarities between cardiac and music rhythms, I match the heart rhythms to music with similar rhythms to form assemblage pieces. The use of music notation leads to representations that enable formal comparisons and automated as well as human-readable analysis of the time structures of performed music and of arrhythmia ECG sequences beyond what is currently possible.

Exploring the effect of tempo changes on violinists’ body movements

In expressive music performance, tempo is known to be a fundamental parameter. In this article, we explored effects of changes in musical tempo on performers’ movement articulations. Eight duos (piano – violin) played two pieces at a predefined tempo, after which this start tempo was gradually increased and decreased. Throughout the different performances, we measured acceleration of the violinists’ head and right wrist, together with the downward force applied by their body to the ground surface. We calculated periodicities in downward force using fast Fourier transform (FFT) analyses and tested whether differences occurred across different tempi. Also, we clustered acceleration and force patterns across different tempi using self-organizing maps (SOMs) and k-means clustering. The results show that a continuous change in performance tempo leads to distinct “performance states” with characteristic bodily behavior in terms of periodic body movement and co-articulated gestures, which supports theories of tempo-variant motor control.

Expressiveness in Music Performance: Empirical Approaches across Styles and Cultures. Ed. by Dorottya Fabian, Renee Timmers, and Emery Schubert

This is an excellent and weighty collection of essays by a group of distinguished writers representing a wide spectrum of performance studies. The book is superbly edited, nicely produced, and comes with helpful sound clips on an associated website. While I highly commend the book as a whole, I do have reservations about some of the angles it takes, although these pertain as much to orientations in the discipline in general as to the volume at hand. Leaving aside the question as to whether or not performance studies has actually come of age as a discipline, one could argue that it has still not acquired a theory. And yet, ironically, for lack of a theory, many of its presuppositions have hardened into doctrine, if not dogma. Two presuppositions advocated by most of the contributors to this collection are flagged up in the editors’ introduction. The first is that ‘expressiveness’ inheres in the way music is performed, rather than in any of its structural features. Thus expressiveness is held to be variation of auditory parameters relative to a prototypical performance (emphatically not the score, even if there is one). The second definition is that expressiveness is engendered by deviation or irregularity, instead of residing within any performance idiom in itself. A corollary of this is that expressiveness is intransitive, so doesn’t need to express a particular emotion or mood (happy, sad, etc.). Both axioms are highly contestable, but not significantly contested by the twenty-two contributors who were invited to shape their texts around the editors’ definition of expressiveness. I’ll return to that at the end of this review, in the light of everything the authors have to say.

Dorottya Fabian, Renee Timmers and Emery Schubert, eds, Expressiveness in Music Performance: Empirical Approaches across Styles and Cultures (Oxford: Oxford University Press, 2014). xxx + 383 pp. £55.00.

Dorottya Fabian, Renee Timmers and Emery Schubert, eds, Expressiveness in Music Performance: Empirical Approaches across Styles and Cultures (Oxford: Oxford University Press, 2014). xxx + 383 pp. £55.00.

Instrumental teachers’ instructional strategies for facilitating children’s learning of expressive music performance: An exploratory study

This article presents findings from an action research project that investigated instrumental teachers’ strategies for facilitating children’s learning of expressive music performance. Nine teachers and 14 pupils (aged 9–15) participated in this project, which consisted of 10 weeks of teaching. At the beginning and end of this period pupils’ concerts were held and performances were audio-recorded. Participating teachers used various strategies for improving students’ expressive performance: teacher’s enquiry, discussion, explanation of expressive devices, gestures and movements, singing, imagery, modelling, “projected performance” and listening to own recordings. According to teachers these strategies had been useful in lessons. However, analysis of assessments of students’ performances did not show a significant improvement. Four out of five pupils who did improve their expressiveness were taught by teachers who used enquiry and discussion of musical character and instruction about modifying expressive devices. This project influenced the practice of participating tutors as they focused more on teaching expressive performance.

A machine learning approach to ornamentation modeling and synthesis in jazz guitar

We present a machine learning approach to automatically generate expressive (ornamented) jazz performances from un-expressive music scores. Features extracted from the scores and the corresponding audio recordings performed by a professional guitarist were used to train computational models for predicting melody ornamentation. As a first step, several machine learning techniques were explored to induce regression models for timing, onset, and dynamics (i.e. note duration and energy) transformations, and an ornamentation model for classifying notes as ornamented or non-ornamented. In a second step, the most suitable ornament for predicted ornamented notes was selected based on note context similarity. Finally, concatenative synthesis was used to automatically synthesize expressive performances of new pieces using the induced models. Supplemental online material for this article containing musical examples of the automatically generated ornamented pieces can be accessed at doi: 10.1080/17459737.2016.1207814 and https://soundcloud.com/machine-learning-and-jazz. In the Online Supplement we present an example of the musical piece Yesterdays by Jerome Kern, which was modeled using our methodology for expressive music performance in jazz guitar.

Expressiveness in musical performance: Pedagogic aspect

The subject of our research relates to pedagogic aspects of expressive vocal-instrumental musical performance. We intended to examine: (1) how undergraduate students see/conceptualize and evaluate expressiveness in musical performance; (2) whether and how they were trained in the skill of expressive musical performance during their musical training; (3) whether and in which way they rehearse the expressive component of musical performance and interpretation and (4) whether there are any differences regarding gender, age, instrument, department, year of study and years of instrument playing in relation to the group of dependant variables related to expressiveness, tuition and practice. The sample for the research included 82 students of instrumental and theory departments at the Faculty of Music in Belgrade. Psychological and pedagogical aspects of musical expressiveness during vocal-instrumental performance were analyzed. The results show that students highly evaluate expressiveness but its place is secondary compared to mastering technical and tonal requirements. Statistically significant differences were shown regarding gender, age and departments. It can be concluded that there is a potential for the development and enhancement of expressiveness of students if we abandon the traditional view that expressiveness is linked exclusively to talent. The findings indicate that pedagogical work should be directed towards finding purposeful strategies for training individual expressiveness.

Contrôle gestuel de la synthèse vocale. Les instruments Cantor Digitalis et Digitartic

EXTENDED ABSTRACT: Gestural control of speech or singing synthesis is difficult, because of the very fast articulators motions encountered in speech and singing. For singing, another difficult question is accurate rhythmic coordination and precision, because syllables must coincide with musical beats, at a given tempo. Then, the precise location of beats for different syllables must be controlled. Two singing synthesis instruments are presented: Digitalis Cantor and Digitartic. Both instruments use bimanual writing or drawing gestures on graphic tablets. The voice signal is computed with the help of a parametric synthesizer, including a voice source model, consonantal noise models and series/parallel formant filters. Cantor Digitalis is a vowel and semi-vowel singing instrument. Digitartic is an extension of Cantor Digitalis and allows for singing syllables, including plosives, fricative, liquid and nasal consonants. Any in-between canonical place of articulation is possible by linear interpolation of the consonant parameters, for each mode of articulation. In this paper, the focus is given on Digitartic through the issue of consonant gestures and musical beat synchronization. Three modes of Vowel-Consonant-Vowel (VCV) articulation are discussed according to three levels of rhythmic precision and musical context. A VCV articulation is composed of the onset phase (articulators approaching the position of maximum constriction), the medial phase (maximum of constriction) and the offset phase (constriction release). Offset phase of plosives is very short compared to other consonants. The first control mode consists of triggering the syllable at the beginning of the onset phase. However, when the syllable starts on the musical beat, it is perceived with a delay depending on the duration of articulation phases. Anticipating precisely this delay is very difficult. The second control mode of control allows for triggering the VCV dissyllable in two steps. In the first step, the onset phase is triggered, and in the second step, the offset phase is triggered. In this way, plosives can be synchronized with musical beats without any delay. The third control mode is a continuous control of the phases of articulation, without any triggering. This requires a fast synthesis engine, a high interface sampling rate, as well as an expert control gesture, fast and precise enough to reproduce speech articulation phases. The continuous control mode of articulation is performed by a back-and-forth gesture with the pen of the non-preferred hand, along the vertical dimension of the graphic tablet. Place of articulation is continuously controlled along the horizontal dimension, and the mode of articulation is assigned to different areas on the tablet. This back-and-forth gesture is analog to the somewhat symmetric articulation of the VCV dissyllable. The gesture amplitude allows for different degrees of articulation (hypoarticulation to hyperarticulation). Controlling durations of each phase of articulation is another mean to increase expressiveness. The preferred hand is controlling pitch, vocal effort and vowel quality on another graphic tablet. Then it is possible to modify pitch and vocal effort during each phase of articulation. Cantor Digitalis and Digitartic allow for expressive musical performances. They are regularly used for concerts.

Book review: Expressiveness in music performance: Empirical approaches across styles and cultures Oxford. By D. Fabian, R. Timmers, & E. Schubert (Eds.)

Book review: Expressiveness in music performance: Empirical approaches across styles and cultures Oxford. By D. Fabian, R. Timmers, & E. Schubert (Eds.)

Review of Expressiveness in music performance: Empirical approaches across styles and cultures.

Review of Expressiveness in music performance: Empirical approaches across styles and cultures.

World Stage: Crowdsourcing Paradigm for Expressive Social Mobile Music

The combination of powerful mobile devices and the connective potential of cloud-based computing are changing how, where, and when people use computers. No longer physically tethered, computers embedded in mobile phones and tablets freely roam in daily life alongside their human users while persistently connected to the network. At the same time, the pervasiveness of computing enables us to engage people to solve large-scale problems by leveraging human intelligence and the effect of large crowds. In this paper, we discuss a new model for crowdsourced musical interactions based on mobile devices. This model, which we call World Stage, is a pseudo-anonymous, location-aware ecosystem designed to connect hundreds of thousands of users in a social-musical game involving expressive musical performance and collaborative musical feedback. We describe the motivation and mechanics of the World Stage, and present a full implementation and case study around a commercial iPhone application: Smule’s Leaf Trombone: World Stage. We also present the experiential design and the technological infrastructure around the World Stage and discuss the unique social/musical possibilities it affords. This work is about exploring, perhaps for the very first time, a crowdsourcing eco-system that incorporates expressive music-making and with game-like elements, aimed at inciting a mass audience.

Book Review: Dorottya Fabian, Renee Timmers, and Emery Schubert (eds) Expressiveness in Music Performance: Emprical Approaches across Styles and Cultures

Book Review: Dorottya Fabian, Renee Timmers, and Emery Schubert (eds) <i>Expressiveness in Music Performance: Emprical Approaches across Styles and Cultures</i>

CaRo 2.0: An Interactive System for Expressive Music Rendering

In several application contexts in multimedia field (educational, extreme gaming), the interaction with the user requests that system is able to render music in expressive way. The expressiveness is the added value of a performance and is part of the reason that music is interesting to listen. Understanding and modeling expressive content communication is important for many engineering applications in information technology (e.g., Music Information Retrieval, as well as several applications in the affective computing field). In this paper, we present an original approach to modify the expressive content of a performance in a gradual way, applying a smooth morphing among performances with different expressive content in order to adapt the audio expressive character to the user’s desires. The system won the final stage of Rencon 2011. This performance RENdering CONtest is a research project that organizes contests for computer systems generating expressive musical performances.

The Role of Individual Difference in Judging Expressiveness of Computer-Assisted Music Performances by Experts

Computational systems for generating expressive musical performances have been studied for several decades now. These models are generally evaluated by comparing their predictions with actual performances, both from a performance parameter and a subjective point of view, often focusing on very specific aspects of the model. However, little is known about how listeners evaluate the generated performances and what factors influence their judgement and appreciation. In this article, we present two studies, conducted during two dedicated workshops, to start understanding how the audience judges entire performances employing different approaches to generating musical expression. In the preliminary study, 40 participants completed a questionnaire in response to five different computer-generated and computer-assisted performances, rating preference and describing the expressiveness of the performances. In the second, “GATM” ( Gruppo di Analisi e Teoria Musicale ) study, 23 participants also completed the Music Cognitive Style questionnaire. Results indicated that music systemizers tend to describe musical expression in terms of the formal aspects of the music, and music empathizers tend to report expressiveness in terms of emotions and characters. However, high systemizers did not differ from high empathizers in their mean preference score across the five pieces. We also concluded that listeners tend not to focus on the basic technical aspects of playing when judging computer-assisted and computer-generated performances. Implications for the significance of individual differences in judging musical expression are discussed.

The Sense of Ensemble: a Machine Learning Approach to Expressive Performance Modelling in String Quartets

Computational approaches for modelling expressive music performance have produced systems that emulate music expression, but few steps have been taken in the domain of ensemble performance. In this paper, we propose a novel method for building computational models of ensemble expressive performance and show how this method can be applied for deriving new insights about collaboration among musicians. In order to address the problem of inter-dependence among musicians we propose the introduction of inter-voice contextual attributes. We evaluate the method on data extracted from multi-modal recordings of string quartet performances in two different conditions: solo and ensemble. We used machine-learning algorithms to produce computational models for predicting intensity, timing deviations, vibrato extent, and bowing speed of each note. As a result, the introduced inter-voice contextual attributes generally improved the prediction of the expressive parameters. Furthermore, results on attribute selection show that the models trained on ensemble recordings took more advantage of inter-voice contextual attributes than those trained on solo recordings.

Human-computer music performance: A brief history and future prospects

Computer accompaniment began in the eighties as a technology to synchronize computers to live musicians by sensing, following, and adapting to expressive musical performances. The technology has progressed from systems where performances were modeled as sequences of discrete symbols, i.e., pitches, to modern systems that use continuous probabilistic models. Although score following techniques have been a common focus, computer accompaniment research has addressed many other interesting topics, including the musical adjustment of tempo, the problem of following an ensemble of musicians, and making systems more robust to unexpected mistakes by performers. Looking toward the future, we find that score following is only one of many ways musicians use to synchronize. Score following is appropriate when scores exist and describe the performance accurately, and where timing deviations are to be followed rather than ignored. In many cases, however, especially in popular music forms, tempo is rather steady, and performers improvise many of their parts. Traditional computer accompaniment techniques do not solve these important music performance scenarios. The term Human-Computer Music Performance (HCMP) has been introduced to cover a broader spectrum of problems and technologies where humans and computers perform music together, adding interesting new problems and directions for future research.

Visualization of time-varying joint development of pitch and dynamics for speech emotion recognition

In this paper, we propose a new approach for visualizing the time-varying acoustic features for speech emotion recognition. Although the emotional state does not carry any linguistic information, it is a crucial factor that offers sentiment feedback to the listener. We propose to extract the two most prevalent acoustic features: pitch and dynamics, to identify the speech emotion of the speaker. We represent the time-varying pitch and dynamics as a trajectory in a two-dimensional feature space. Multiple trajectories are then segmented and clustered into signature patterns. This technique was successful in identifying and retargeting expressive musical performance styles. In evaluation, we use the German emotion language database. The database was created with ten professional actors (five males and five females) of ten emotionally unbiased sentences performed in six target emotions (Angry, Happy, Fear, Boredom, Sad, and Disgust). Results showed that the speech samples from the same actor of the same sentence but different emotions have dramatically different trajectory patterns. On the other hand, obvious common patterns were found among low valence emotions like Boredom and Sadness. The current study also opens future research opportunities for applying advanced pattern recognition techniques (e.g., Support Vector Machine and Neural Network) for better emotion identification.

Dynamic musical communication of core affect.

Is there something special about the way music communicates feelings? Theorists since Meyer (1956) have attempted to explain how music could stimulate varied and subtle affective experiences by violating learned expectancies, or by mimicking other forms of social interaction. Our proposal is that music speaks to the brain in its own language; it need not imitate any other form of communication. We review recent theoretical and empirical literature, which suggests that all conscious processes consist of dynamic neural events, produced by spatially dispersed processes in the physical brain. Intentional thought and affective experience arise as dynamical aspects of neural events taking place in multiple brain areas simultaneously. At any given moment, this content comprises a unified “scene” that is integrated into a dynamic core through synchrony of neuronal oscillations. We propose that (1) neurodynamic synchrony with musical stimuli gives rise to musical qualia including tonal and temporal expectancies, and that (2) music-synchronous responses couple into core neurodynamics, enabling music to directly modulate core affect. Expressive music performance, for example, may recruit rhythm-synchronous neural responses to support affective communication. We suggest that the dynamic relationship between musical expression and the experience of affect presents a unique opportunity for the study of emotional experience. This may help elucidate the neural mechanisms underlying arousal and valence, and offer a new approach to exploring the complex dynamics of the how and why of emotional experience.

Can Micro-Gestural Inflections Be Used to Improve the Soniculatory Effectiveness of Parameter Mapping Sonifications?

Parameter mapping sonification is the most widely used technique for representing multi-dimensional data in sound. However, it is known to be unreliable when used for detecting information in some types of data. This is generally thought to be the result of the co-dependency of the psychoacoustic dimensions used in the mapping.Positing its perceptual basis in a theory of embodied cognition, the most common approach to overcoming this limitation involves techniques that afford the interactive exploration of the data using gross body gestures. In some circumstances, such exploration is not possible and, even when it is, it may be neither necessary nor sufficient.This article explores some other possible reasons for the unreliability of parameter mapping sonification and, drawing from the experience of expressive musical performance, suggests that the problem lies not in the parametric approachper se, nor in the lack of interactivity, but in the extent to which the parameters employed contribute to coherent gestalts. A method for how this might be achieved that relies on the use of micro-gestural information is proposed. While this is speculative, the use of such gestural inflections is well known in music performance, is supported by findings in neuroscience and lends itself to empirical testing.