Analysing musical performance through functional data analysis: rhythmic structure in Schumann's Träumerei

Functional data analysis (FDA) is a relatively new branch of statistics devoted to describing and modelling data that are complete functions. Many relevant aspects of musical performance and perception can be understood and quantified as dynamic processes evolving as functions of time. In this paper, we show that FDA is a statistical methodology well suited for research into the field of quantitative musical performance analysis. To demonstrate this suitability, we consider tempo data for 28 performances of Schumann's Träumerei and analyse them by means of functional principal component analysis (one of the most powerful descriptive tools included in FDA). Specifically, we investigate the commonalities and differences between different performances regarding (expressive) timing, and we cluster similar performances together. We conclude that musical data considered as functional data reveal performance structures that might otherwise go unnoticed.Peer ReviewedPostprint (author's final draft

A Novel Interface for the Graphical Analysis of Music Practice Behaviors

Practice is an essential part of music training, but critical content-based analyses of practice behaviors still lack tools for conveying informative representation of practice sessions. To bridge this gap, we present a novel visualization system, the Music Practice Browser, for representing, identifying, and analysing music practice behaviors. The Music Practice Browser provides a graphical interface for reviewing recorded practice sessions, which allows musicians, teachers, and researchers to examine aspects and features of music practice behaviors. The system takes beat and practice segment information together with a musical score in XML format as input, and produces a number of different visualizations: Practice Session Work Maps give an overview of contiguous practice segments; Practice Segment Arcs make evident transitions and repeated segments; Practice Session Precision Maps facilitate the identifying of errors; Tempo-Loudness Evolution Graphs track expressive variations over the course of a practice session. We then test the new system on practice sessions of pianists of varying levels of expertise ranging from novice to expert. The practice patterns found include Drill-Correct, Drill-Smooth, Memorization Strategy, Review and Explore, and Expressive Evolution. The analysis reveals practice patterns and behavior differences between beginners and experts, such as a higher proportion of Drill-Smooth patterns in expert practice

Measuring Expressive Music Performances: a Performance Science Model using Symbolic Approximation

Music Performance Science (MPS), sometimes termed systematic musicology in Northern Europe, is concerned with designing, testing and applying quantitative measurements to music performances. It has applications in art musics, jazz and other genres. It is least concerned with aesthetic judgements or with ontological considerations of artworks that stand alone from their instantiations in performances. Musicians deliver expressive performances by manipulating multiple, simultaneous variables including, but not limited to: tempo, acceleration and deceleration, dynamics, rates of change of dynamic levels, intonation and articulation. There are significant complexities when handling multivariate music datasets of significant scale. A critical issue in analyzing any types of large datasets is the likelihood of detecting meaningless relationships the more dimensions are included. One possible choice is to create algorithms that address both volume and complexity. Another, and the approach chosen here, is to apply techniques that reduce both the dimensionality and numerosity of the music datasets while assuring the statistical significance of results. This dissertation describes a flexible computational model, based on symbolic approximation of timeseries, that can extract time-related characteristics of music performances to generate performance fingerprints (dissimilarities from an ‘average performance’) to be used for comparative purposes. The model is applied to recordings of Arnold Schoenberg’s Phantasy for Violin with Piano Accompaniment, Opus 47 (1949), having initially been validated on Chopin Mazurkas.1 The results are subsequently used to test hypotheses about evolution in performance styles of the Phantasy since its composition. It is hoped that further research will examine other works and types of music in order to improve this model and make it useful to other music researchers. In addition to its benefits for performance analysis, it is suggested that the model has clear applications at least in music fraud detection, Music Information Retrieval (MIR) and in pedagogical applications for music education

Affective communication remapping in MusicFace System

This paper addresses the issue of affective communication remapping, i.e. translation of affective content from one communication form to another. We propose a method to extract the affective data from a piece of music and then use that to animate a face. The method is based on studies of emotional aspect of music and our behavioural head model for face animation

Audio-Based Visualization of Expressive Body Movements in Music Performance: An Evaluation of Methodology in Three Electroacoustic Compositions

An increase in collaboration amongst visual artists, performance artists, musicians, and programmers has given rise to the exploration of multimedia performance arts. A methodology for audio-based visualization has been created that integrates the information of sound with the visualization of physical expressions, with the goal of magnifying the expressiveness of the performance. The emphasis is placed on exalting the music by using the audio to affect and enhance the video processing, while the video does not affect the audio at all. In this sense the music is considered to be autonomous of the video. The audio-based visualization can provide the audience with a deeper appreciation of the music. Unique implementations of the methodology have been created for three compositions. A qualitative analysis of each implementation is employed to evaluate both the technological and aesthetic merits for each composition