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Enhancing Orchestration Technique via Spectrally Based Linear Algebra Methods
Computer Music Joual, 33:1, pp. 32–41, Spring 2009.
c 2009 Massachusetts Institute of Technology.
Franc?ois Rose? and James E. Hetrick†.
?Conservatory of Music.
†Physics Department.
University of the Pacific.
3601 Pacific Avenue.
Stockton, Califoia 95211 USA.
Spectral analysis has a rich and central place in the.
history and understanding of music, and mode.
music production relies heavily upon it. However,
the advanced use of Fourier techniques as an aid.
to composition—as opposed to a tool for signal.
processing or sound synthesis—has been relatively.
unexplored until recently (Carpentier et al. 2006,
2007; Carpentier, Tardieu, and Rodet 2007; Hummel.
2005; Psenicka 2003; Rose and Hetrick 2005, 2007).
Because orchestration is the vehicle that carries a.
musical idea from imagination to reality, it is clear.
that composers’ orchestration techniques have a.
major impact on their musical expressions. Spectral.
analysis, by providing essential information about.
sound mixtures that are new or that are subject to.
constraints, can profoundly and positively influence.
that technique.
In this article, we present our approach to.
such a computerized aid that extends the use.
of spectral analysis for orchestration. It uses a.
bank of Discrete Fourier Transforms (DFTs) of.
orchestral sounds, which are accessed in different.
ways designed to either perform sound analysis or.
propose orchestrations that imitate the energetic.
patte of a reference sound. The output of the tool.
is a weighted set of all possible sound mixtures from.
the palette, a subset of the complete bank—typically.
instruments for which the composer is writing.
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