2010•Journal of New Music ResearchRequires access

Predicting Timbre Features of Instrument Sound Combinations: Application to Automatic Orchestration

Grégoire Carpentier, Damien Tardieu, Jonathan P. Harvey, Gérard Assayag, Emmanuel Saint-James

Open publisher page 18 citations

Abstract

In this paper we first introduce a set of functions to predict the timbre features of an instrument sound combination, given the features of the individual components in the mixture. We then compare, for different classes of sound combinations, the estimated values of the timbre features to real measurements and show the accuracy of our predictors. In the second part of the paper, we present original musical applications of feature prediction in the field of computer-aided orchestration. These examples all come from real-life compositional situations, and were all produced with Orchidée, an innovative framework for computer-aided orchestration recently designed and developed at IRCAM, Paris.

About this research paper

What this paper is about

In this paper we first introduce a set of functions to predict the timbre features of an instrument sound combination, given the features of the individual components in the mixture. We then compare, for different classes of sound combinations, the estimated values of the timbre features to real measurements and show the accuracy of our predictors. In the second part of the paper, we present original musical applications of feature prediction in the field of computer-aided orchestration. These examples all come from real-life compositional situations, and were all produced with Orchidée, an innovative framework for computer-aided orchestration recently designed and developed at IRCAM, Paris.

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OpenAlex reports 18 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper we first introduce a set of functions to predict the timbre features of an instrument sound combination, given the features of the individual components in the mixture. We then compare, for different classes of sound combinations, the estimated values of the timbre features to real measurements and show the accuracy of our predictors. In the second part of the paper, we present original musical applications of feature prediction in the field of computer-aided orchestration. These examples all come from real-life compositional situations, and were all produced with Orchidée, an innovative framework for computer-aided orchestration recently designed and developed at IRCAM, Paris.

Key concepts: Timbre, Orchestration, Computer science, Set (abstract data type), Feature (linguistics), Field (mathematics), Sound (geography), Musical instrument

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