Predicting Timbre Features of Instrument Sound Combinations: Application to Automatic Orchestration
Grégoire Carpentier, Damien Tardieu, Jonathan P. Harvey, Gérard Assayag, Emmanuel Saint-James
Abstract
Grégoire Carpentier, Damien Tardieu, Jonathan P. Harvey, Gérard Assayag, Emmanuel Saint-James
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.
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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