An Evolutionary Approach to Computer-Aided Orchestration

Abstract

Abstract. In this paper we introduce an hybrid evolutionary algorithm for computer-aided orchestration. Our current approach to orchestration consists in replicating a target sound with a set of instruments sound samples. We show how the orchestration problem can be viewed as a multi-objective 0/1 knapsack problem, with additional constraints and a case-specific criteria formulation. Our search method hybridizes genetic search and local search, for both of which we define ad-hoc genetic and neighborhood operators. A simple modelling of sound combinations is used to create two new mutation operators for genetic search, while a preliminary clustering procedure allows for the computation of sound mixtures neighborhoods for the local search phase. We also show in which way user interaction might be introduced in the orchestration procedure itself, and how to lead the search according to the users choices.

Perception of Dyads of Impulsive and Sustained Instrument Sounds

“…To help the composer explore the timbral possibilities of the orchestra, we propose the following problem: Given a target sound, how do we find a combination of instrument notes that sounds close to this target (for more details concerning this problem see Carpentier, Tardieu, Assayag, Rodet, & Saint-James, 2007;Tardieu & Rodet, 2007). This problem raises many questions, some of which we address here: How is a combination of instrument tones perceived in terms of blend and emergent timbre?…”

Computer-Aided Musical Orchestration Using an Artificial Immune System

“…The work of Carpentier et al [3][4][5][6]19] represents a paradigm shift in CAMO. Prior to their work, most approaches [11,17,18] used greedy search procedures based on subtractive spectral matching.…”

“…Compositional experimentation in orchestration arises from the increasing tendency to specify instrument combinations to achieve desired effects, resulting in the contemporary use of timbral combinations [15,18]. The development of computational tools that aid the composer in exploring the virtually infinite possibilities resulting from the combinations of musical instruments gave rise to computer-aided musical orchestration (CAMO) [3][4][5][6]11,17,18]. Most of these tools rely on searching for combinations of musical instrument sounds from pre-recorded datasets to approximate a given target sound.…”

“…To overcome the drawbacks of subtractive spectral matching, Carpentier and collaborators [3][4][5][6]19] search for a combination of musical instrument sounds whose timbral features best match those of the target sound. This approach requires a model of timbre perception to describe the timbre of isolated sounds, a method to estimate the timbral result of an instrument combination, and a measure of timbre similarity to compare the combinations and the target.…”

“…Carpentier and collaborators [3][4][5][6]19] consider the search for combinations of musical instrument sounds as a constrained combinatorial optimization problem [5]. They formulate CAMO as a variation of the knapsack problem where the aim is to find a combination of musical instruments that maximizes the timbral similarity with the target constrained by the capacity of the orchestra (i.e., the database).…”