SOURCE-LINKED INTELLIGENCE
Engineering voice-based models and interfaces for enhancing the speech therapy of minimally-verbal children with autism and their communication
loit the obtained knowledge to create advanced voice-based interfaces to enhance their therapeutic interventions. During the outgoing phase at MIT, the work will be about identifying and implementing machine learning algorithms for classifying children's vocalizations. The core strategy is to leverage the unique knowledge provided by caregivers who have long-term acquaintance with MV children with autism and can recognize the meaning of their vocalizations. In the return phase at POLIMI, the project will be about designing, developing, and empirically validating a voice-based AAC prototype for children's speech therapy through a participatory-design process involving end users, their caregivers, and autism experts. Audio signal processing, Deep Neural Network, Voice-based interaction, Computer-assisted therapy, Autism
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- recordType
- award
- status
- TERMINATED
- region
- EU
- value
- 175737.12
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T01:21:06.728Z. This is not the publication date.