Project description
Better understanding of sound
Humans can recognise speech, music and environmental sounds rapidly, even in noisy or unpredictable settings. Current AI systems still struggle with this flexibility because they often learn from static datasets rather than processing sound dynamically like the brain. With the support of the Marie Skłodowska-Curie Actions programme, the SONATA project will use recordings of human brain activity to design smarter AI systems for sound recognition. Using magnetoencephalography, which measures brain signals with millisecond precision, researchers will compare how the brain and AI models represent sounds. These insights will guide the creation of biologically inspired neural networks. Project outcomes could advance neuroscience, improve assistive hearing technologies and strengthen audio-based AI applications.
Objective
SONATA (Sound-Oriented Neural-AI Alignment for Temporal Audition) addresses a core scientific and technological challenge: artificial systems still lack the human brain’s ability to interpret sounds quickly and flexibly. While the brain extracts meaning from sound through dynamic, multiscale processing, current AI systems are trained on static datasets and often fail in unpredictable or noisy conditions. SONATA proposes a new strategy: using high-resolution brain data to guide the development of deep learning models for sound recognition. Specifically, it develops biologically inspired multistream neural networks and constrains their architecture using recordings from magnetoencephalography (MEG), a non-invasive technique that captures brain activity with millisecond precision. The key innovation lies in integrating tools from cognitive neuroscience—such as Representational Similarity Analysis—into the training and evaluation pipeline. These techniques allow the project to align internal model representations with those observed in the brain. The action is structured around three objectives: (O1) design of neuro-inspired model architectures; (O2) incorporation of both theoretical and data-driven neural constraints; and (O3) dual benchmarking of functional accuracy and biological plausibility. SONATA is hosted at Aix-Marseille Université under the supervision of Dr. Bruno Giordano, and will generate open-source tools and insights with applications in auditory neuroscience, AI, and assistive hearing technologies.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences neurobiology
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- natural sciences computer and information sciences artificial intelligence computational intelligence
You need to log in or register to use this function
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
See all projects funded under this callCoordinator
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
13284 Marseille
France
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.