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Generative Compositional Assistant for Sketching Textures

Project description

Defining authorship in human-AI musical interaction

Supported by the Marie Skłodowska-Curie Actions programme, the GenCAST project will focus on developing an artificial intelligence assistant that prioritises human authorship and control during the musical composition process. Unlike many current tools that rely on opaque prompts, this project will use symbolic modelling to help musicians manipulate complex musical textures and layers. By creating a variational autoencoder model and a dedicated software plugin, GenCAST aims to offer composers a more interactive way to reshape their work. Additional objectives include bridging the gap between advanced technology and traditional musicological research, as well as empowering artists by integrating creative practice with sophisticated, user-centred AI frameworks.

Objective

GenCAST explores how artificial intelligence can support musical creativity by addressing a key challenge in human–AI interaction: the question of authorship and control. It focuses on musical texture — the way elements such as melodies, rhythms, timbres are layered and combined in time, from a single melodic line to complex polyphonic structures — as a central dimension of musical modelling. The project investigates how symbolic representations of texture can inform the design of a composition assistant that enables meaningful and controllable musical transformations.

At a time when AI tools are reshaping creative workflows, recent advances — from generative audio models to real-time improvisation frameworks — have expanded the ways musicians interact with technology. Yet most recent industry solutions rely on opaque, prompt-based processes with little connection to symbolic musical structure. In response, GenCAST proposes a musician-centred assistant grounded in symbolic modelling, bridging AI and musicological knowledge.

The project will curate a symbolic dataset, train a variational autoencoder (VAE) model, and integrate it into a composition plugin enabling composers to explore, combine, and reshape textures interactively. Validation with users will ensure both scientific and artistic relevance.

The fellowship will be hosted at Maynooth University under the supervision of Prof. Victor Lazzarini, whose team combines musicological research with software development — an ideal context for mutual exchange with the fellow's expertise in texture modelling and AI. A secondment at STMS-IRCAM (France) under the supervision of Dr. Gérard Assayag will connect the project to a leading academic and artistic communities. This project will establish the fellow's profile as a researcher working at the intersection of musicology, technology and creative practice, enhancing their prospects for future roles in academia and industry.

Fields of science (EuroSciVoc)

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Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

NATIONAL UNIVERSITY OF IRELAND MAYNOOTH
Net EU contribution
€ 252 728,64
Address
CO KILDARE
W23 Maynooth
Ireland
Region
Ireland Eastern and Midland Mid-East
Activity type
Higher or Secondary Education Establishments
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Total cost
No data

Partners (1)