Affective evolutionary music composition with MetaCompose

Marco Scirea, Julian Togelius, Peter Eklund, Sebastian Risi

    Research output: Contribution to journalArticle

    Abstract

    This paper describes the MetaCompose music generator,a compositional, extensible framework for affective music composition. In this context ‘affective’ refers to the music generator’s ability to express emotional information. The main purpose of MetaCompose is to create music in real-time that can express different mood-states, which we achieve through a unique combination of a graph traversal-based chord sequence generator, a search-based melody generator, a pattern-based accompaniment generator, and a theory for mood expression. Melody generation uses a novel evolutionary technique combining FI-2POP with multi-objective optimization. This allows us to explore a Pareto front of diverse solutions that are creatively equivalent under the terms of a multi-criteria objective function. Two quantitative user studies were performed to evaluate the system: one focusing on the music generation technique, and the other that explores valence expression,via the introduction of dissonances. The results of these studies demonstrate (i) that each part of the generation system improves the perceived quality of the music produced, and (ii) how valence expression via dissonance produces the perceived affective state. This system, which can reliably generate affect-expressive music, can subsequently be integrated in any kind of interactive application (e.g., games) to create an adaptive and dynamic soundtrack.

    Original languageEnglish (US)
    Pages (from-to)1-33
    Number of pages33
    JournalGenetic Programming and Evolvable Machines
    DOIs
    StateAccepted/In press - Jun 9 2017

    Fingerprint

    Multiobjective optimization
    Music
    Generator
    Chemical analysis
    Mood
    Express
    Pareto Front
    User Studies
    Multi-criteria
    Chord or secant line
    Multi-objective Optimization
    Objective function
    Game
    Real-time
    Evaluate
    Term
    Graph in graph theory
    Demonstrate

    Keywords

    • Affective music
    • Creative computing
    • Evolutionary computing
    • Genetic algorithm
    • Music generation

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Software
    • Hardware and Architecture
    • Computer Science Applications

    Cite this

    Affective evolutionary music composition with MetaCompose. / Scirea, Marco; Togelius, Julian; Eklund, Peter; Risi, Sebastian.

    In: Genetic Programming and Evolvable Machines, 09.06.2017, p. 1-33.

    Research output: Contribution to journalArticle

    Scirea, Marco ; Togelius, Julian ; Eklund, Peter ; Risi, Sebastian. / Affective evolutionary music composition with MetaCompose. In: Genetic Programming and Evolvable Machines. 2017 ; pp. 1-33.
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