One of the most complex and mysterious aspects of musical composition, still scarcely studied in the scientific domain, concerns writing timbre, in particular orchestration techniques. The project is based on a comparison of the state of the art in musicology, in psychology of perception, and in computer music to create new tools to address problems connected to orchestration, its perception, and its instruction.
The objective is to develop models that can be generalized, that facilitate the instruction and practice of orchestration, assisted by new technologies. The long-term goal is to create an interactive treaty on orchestration comprising knowledge on orchestration practices, the perception of orchestral effects, and digital tools to help resolve orchestration problems including writing electronic sections of mixed-music works. The project relies on a large quantity of annotations made on the corpus of classical music using a range of pertinent categories, intended to supply both perceptive experiences and educational materials as well as to establish practice data for automatic learning algorithms.
IRCAM’s role in this project focuses on computer music applications and artificial intelligence for computer-assisted orchestration tools based on the software program Orchids and new research on deep learning techniques.