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    The fundamental principle of IRCAM is to encourage productive interaction among scientific research, technological developments, and contemporary music production. Since its establishment in 1977, this initiative has provided the foundation for the institute’s activities. One of the major issues is the importance of contributing to the renewal of musical expression through science and technology. Conversely, sp…

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  • Research

    The fundamental principle of IRCAM is to encourage productive interaction among scientific research, technological developments, and contemporary music production. Since its establishment in 1977, this initiative has provided the foundation for the institute’s activities. One of the major issues is the importance of contributing to the renewal of musical expression through science and technology. Conversely, sp…

    • Research Topics
    • The STMS Lab
    • Research Teams
    • Sound Systems and Signals: Audio/Acoustics, InstruMents
    • Acoustic and Cognitive Spaces
    • Perception and Sound Design
    • Sound Analysis-Synthesis
    • Sound Music Movement Interaction
    • Musical Representations
    • Analysis of Musical Practices
    • Projects
    • Sound Workshop
    • The Musical Body
    • Creative Dynamics
    • Musique/Sciences Collection
  • Creation

    IRCAM is an internationally recognized research center dedicated to creating new technologies for music. The institute offers a unique experimental environment where composers strive to enlarge their musical experience through the concepts expressed in new technologies.

    • Composers & Artists in Studio
    • "I am in blood" for Sixteen Musicians and Live Electronics
    • Lucie Antunes in studio
    • Deena Abdelwahed in the studio
    • "Transfer" for 10 Musicians and Electronics
    • L'Annonce faite à Marie
    • In Ex Machina
    • Jazz Ex Machina
    • Improvise cum machina 1/2
    • Improvise cum machina 2/2
    • Like Sound, Like Flesh
    • Silent Talks
    • Music-Fictions
    • Artistic Research Residency
    • Artistic Residencies: The Blog
    • Rendez Vous 20.21
    • Season 2022.23
    • Seasons from 1996 to present
    • ManiFeste-2022 Website
    • ManiFeste festival from 2012 to 2022
    • L’Étincelle, IRCAM’s journal of creation
  • Transmission

    In parallel to its fundamental missions of research and creation, IRCAM is committed to sharing its knowledge and know-how, its technologies with the general public. Cutting-edge research and diffusion of innovations, an international reference for education and the democratization of artistic practices are the driving forces behind the institute’s educational activities.

    • 2022.23 Training Courses
    • Max, Max for Live
    • OpenMusic
    • Modalys
    • TS2 and Partiels
    • Sound spatialization
    • From PureData to audio plugins
    • Sensors, Interfaces, and Interactive Machine Learning
    • Other training programs
    • Practical Information
    • Advanced Programs
    • Cursus Program on Composition and Computer Music
    • Supersonic Chair
    • Master ATIAM
    • Sound Design Master's Program
    • Music Doctorate
    • AIMove Master
    • School Programs
    • Studios of Creation
    • Mixed-Music
    • Artistic and Cultural Education
    • Career Discovery Visit
    • Images of a Work Collection
    • ManiFeste-2022, the Academy
  • Innovations

    At the center of societal and economic concerns combining culture and information technologies, the current research at IRCAM is seen by the international research community as a reference for interdisciplinary projects on the sciences and technologies for sound and music, constantly exposed to society’s new needs and uses.

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  • Léopold Crestel's PhD Defense








Wed 19 December 2018,
2:30 p.m.
Ircam
salle Stravinsky

Free entry, limited seats available.

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Research
Thesis Defense






Léopold Crestel's PhD Defense

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"Neural networks for automatic musical projective orchestration"
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Orchestration is the art of composing a musical discourse over a combinatorial set of instrumental possibilities. For centuries, musical orchestration has only been addressed in an empirical way, as a scientific theory of orchestration appears elusive. Indeed, whereas harmony and counterpoint can rely on solid theoretical grounds, orchestration remains taught from collections of examples drawn from the repertoire.

In this work, we address these questions within the machine learning framework, by proposing the first projective orchestration system. Hence, we start by formalizing this novel task. We focus our effort on projecting a piano piece (seen as an harmonic draft) onto a full symphonic orchestra, in the style of notable classic composers such as Haydn, Mozart or Beethoven. Hence, the first objective is to design a system of live orchestration, which takes as input the sequence of chords played by a pianist and generate in real-time its orchestration. Afterwards, we relax the real-time constraints in order to use slower but more powerful models and to generate scores in a non-causal way, which is closer to the writing process of a human composer.

By observing a large dataset of orchestral music written by composers and their reduction for piano, we hope to be able to capture through statistical learning methods the mechanisms involved in the orchestration of a piano piece. Deep neural networks seem to be a promising lead for their ability to model complex behaviour from a large dataset and in an unsupervised way. More specifically, in the challenging context of symbolic music which is characterized by a high-dimensional target space and few examples, we investigate autoregressive models. At the price of a slower generation process, auto-regressive models allow to account for more complex dependencies between the different elements of the score, which we believe to be of the foremost importance in the case of orchestration.

Léopold Crestel will defend his doctoral  carried out  in the Musical Representationsteam (STMS - IRCAM/CNRS/Sorbonne Université/Ministère de la Culture).

The jury will be composed:

Philippe Esling, Sorbonne Université
Jean-Gabriel Ganascia, Sorbonne Université
Maarten Grachten, Independent consultant
Florence Levé, Université de Picardie Jules Verne
Yan Maresz, CNSMDP
Geoffroy Peeters, Télécom Paristech
Kamel Smaïli, LORIA, Nancy

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