Project description
Teaching machines to hear like humans
In cafés, on trains, in open offices, even the smartest devices falter. Speech-recognition systems misfire in background noise and earbuds stream music that may not be suitable for the ears receiving it. As populations age and noise exposure rises, hearing loss is becoming a public health issue. The ERC-funded InSilicoEars project aims to combine auditory neuroscience with machine learning. It will build a biophysically realistic in-silico ear that mimics how humans process sound. The system will detect early signs of hearing damage and power low-latency, noise-robust audio tools tailored to individual users.
Objective
As the hearing loss epidemic grows due to an aging population and increasing exposure to urban and recreational noise, the demand for accessible, personalized audio solutions has become more urgent. At the same time, the limitations of speech- and audio-driven systems, such as speech recognition and robotics, are becoming clear. These systems struggle in noisy environments, and consumer electronics for speech and music lack adaptation to individual hearing impairments. To address these challenges, the InSilicoEars project aims to transform hearing loss diagnostics, treatments, and machine-learning-based audio applications by leveraging the unique properties of human auditory processing.
InSilicoEars integrates auditory neuroscience with advanced auditory processing models and machine-learning techniques to create a biophysically realistic in-silico auditory framework. This innovative system incorporates neural stochasticity and auditory feedback mechanisms to simulate the complexities of human hearing and its impairments. A groundbreaking approach converts these models into differentiable, neural-network-based, low-latency alternatives capable of seamless operation in closed-loop systems. The resulting systems enable the development of noise-robust, human-like, real-time audio-processing methods tailored for music and speech, while also compensating for early signs of hearing damage. Diagnostic markers for early-onset hearing loss and personalized audio-processing solutions will be experimentally validated with human test subjects.
By bridging auditory neuroscience and machine learning, InSilicoEars is advancing the next generation personalized hearables and audio technologies. These breakthroughs will enhance the accessibility and performance of audio applications, creating solutions customized to individual needs while expanding the capabilities of consumer electronics in complex, noisy environments.
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
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics
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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.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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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-ERC - HORIZON ERC Grants
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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) ERC-2025-COG
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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.
9000 GENT
Belgium
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.