Computer-Assisted Composition
This project addresses the question of orchestration via an automatic search of instrumentation and layering instruments approaching, depending on different acoustic similarity criteria, a target defined by the composer. Current research endeavors to make this dynamic orchestration paradigm heard, according to the targets with sonorous characteristics that vary with time. Realized after the Orchid.e software suite, Orchids is the first complete system in the Orchid* system for temporal computer-assisted orchestration and the optimization of timbre combinations. It provides an ensemble of algorithms making it possible to recreate any sound target that changes over time through a combination of instruments or samples, according to the psycho-acoustic criteria. This can help composers obtain unique timbre colors providing a multitude of effective solutions to best recreate the sound target. Through a large selection of functions, Orchids can also recreate the evolutions and abstract forms of spectral movements. Its results provide multiple orchestra scores that can be organized intuitively in order to quickly construct orchestral and musical ideas. This system provides several approximation algorithms that make it possible to conjointly optimize several timbre features. The advantages of the Orchids system lies in the fact that this approximation can be carried out separately on temporal forms, values, mean values or standard deviations (or any combination of the three) of each psycho-acoustic descriptor.
In addition, users can also manually define a temporal deformation and carry out a multi-target search within several sound segments, making it possible to create full orchestral works in just a few seconds.
The new version of the Orchid* series, Orchidea, developed in the Musical Representations team in collaboration with the Haute .cole de musique de Gen.ve, is based on orchids and is designed to further optimize analysis, research, and interfaces. It is now available in open-source, and offers significant optimizations and greater reliability of results.
In addition to the production of Orchid* flagship software programs, IRCAM’s orchestration project has led to numerous national and international collaborations coordinated by the institute’s Musical Representations team: the ANR MAKIMONO project explores the contributions of artificial intelligence and machine learning to timbral and orchestral synthesis; the Orchestration project funded by the Social Sciences and Humanities Research Council (SSHRC) with the Haute École de musique de Genève (Switzerland) has laid the foundations for a vast international project involving 19 American and European partners, and finally, the ACTOR project that explores all facets of orchestration, from modeling to education and which started in 2019.
IRCAM's Team: Musical Representations