진학프로석·박사 채용 접수 플랫폼

The position offered is a five-year post-doctorate as part of the ERC Advanced Grant G3S project.

Presentation of the G3S project

Machine learning is particularly well suited to dealing with ill-defined problems, where complexity precludes direct solutions; it is therefore of vital importance in the field of music creation, where compositional knowledge is far from explicit. Until now, the generation of sound spaces has often been neglected in the application of AI to music and sound, whereas 3D spatial audio is the subject of major industrial developments and standardisation.

The ERC Advanced Grant project G3S (Generative Spatial Synthesis of Sound and Music), designed by and for musicians and sound creators, will explore generative approaches to spatialization based on machine learning, to break away from the standards that format our ways of creating or perceiving spatiality, by opening up to all the ways and processes of spatial audio. It is positioned in an original way at the rarely explored intersection of spatialisation and AI, the latter considered in a frugal, local and open source way, and within the framework of an international collaborative research and creation network.

From a large set of varied musical pieces proposing a construction of the sound space, from which we will recover the sound engines (represented by the operations on the signal), their multichannel recordings and the semantic descriptions of spatiality, we will train low-dimensional learning models, combining existing neural techniques. These models will be used to generate sound spaces and to explore them by means of user requests, either functional (describing the desired processing) or imitating an audio result, or semantic (describing the desired space). The spatial engines selected by the user can be exported in the form of plugins.

Over five years, the G3S project will implement and articulate four major research objectives: 1) the design of a unified operational representation of existing spatialization engines 2) the proposal of a thesaurus and quantitative measures to describe the spatiality of sound 3) the generation of sound spaces from machine learning 4) the design of user interfaces to explore spatial audio. We will produce open source environments, compatible with audio standards and shared with the computer music community; we will validate them by commissioning composers, creating works, workshops and concerts.

Details of assignments

As part of the project team under the scientific responsibility of P.I. Prof. Alain Bonardi, you will be associated for five years with two other post-docs to carry out original, high-level research, exploring generative approaches to sound spatialisation based on machine learning, largely founded on research-creation methods. The team will also include four PhD students (each working on a subject corresponding to one of the four research objectives mentioned above).

• The general duties of your post will involve contributing to :
  • to the research and research-creation carried out in the G3S project;
  • setting up and running the international collaborative research and creation network with which the G3S project will be in regular contact;
  • the production of project deliverables, including publications and communications;
  • organising and running major scientific, musical and dissemination events to help evaluate and disseminate the results of the project;

This post-doctorate offer is centred on the theme of 'Artificial learning and generativity', which is one of the three areas of the G3S project (the other two being 'Sound spaces/spatialisation in the context of electroacoustic and mixed music' and 'Interactions and interfaces'). The general framework is the design and exploration of sound space synthesis based on learning corpora provided in three forms by the collaborative network of creation centres associated with the project: sound engine circuits in the form of signal operations, multichannel output files, and the semantic description of the desired spatiality.

The aim will be to implement practical IT solutions for learning and generating sound spaces that are compatible with the environments and working habits of sound composers and creators. However, the research work will be fuelled by a reflection on artificial generativity, in relation with the team but also with the professional artists who will be commissioned for the project and, more broadly, the communities of users who will attend the workshops. Finally, the models will need to examine all forms of sound space creation, from point sources to the spatial processing of sound, in which the synthesis (or transformation) of sound is interwoven with its spatial deployment.

Throughout the project, research into artificial learning and generativity will be closely linked to research into the construction and description of sound spaces (in terms of the choice of data manipulated and openness to different approaches to spatialisation) and research into interfaces and interactions (in terms of the choice of ways of exploring the syntheses proposed by the models).

ACTIVITIES

Over the five years of the project, you will be able to consolidate your experience as a young researcher, contribute to publications in the most reputed conferences and journals in the fields covered, grow your international research network (thanks in particular to the project's collaborative network) and meet industrial R&D players.

The general activities of your post-doctorate will be in line with the general missions defined above:

• conducting your post-doctoral research and research-creation, in collaboration with other post-doctoral and doctoral students, under the scientific responsibility of the P.I. of the ERC G3S project. You will take part in the development and musical and sound testing of prototypes for exploring spatiality based on machine learning;
• work on the various project deliverables:
  • production of open source software
  • production of high-level international publications;
• the organisation of workshops for a variety of audiences, study days, leading symposia on the themes of the project, and professional or amateur concerts using the results of the project.

The activities specific to your post-doctoral research will take place within a research-creation framework, in relation with professional artists and, more broadly, the user communities. The subject of artificial learning and generativity will lead you to interact more particularly with the PhD student working on the artificial generation of sound spaces, but also with the three other PhD students working respectively on the generic operational modelling of sound spaces, their description and exploration interfaces. You will have to build up a significant state of the art in the field, and construct models and prototypes that will be tested both in the studio in our 3D dome and in concert.