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Engineering voice-based models and interfaces for enhancing the speech therapy of minimally-verbal children with autism and their communication

Project description

Providing a voice for minimally verbal autistic children

Communication is a fundamental aspect of our lives, but for about 30 % of children with autism who are minimally verbal, it’s a complex challenge. These children mainly use non-verbal vocalisations to express themselves, which are often misunderstood by those who aren’t closely connected to them. With the support of the Marie Skłodowska-Curie Actions programme, the COMUTTI project will combine audio signal processing and human–computer interaction to create advanced voice-based interfaces for speech therapy. Machine learning algorithms will be developed to classify these vocalisations, capitalising on the unique insights of caregivers. A voice-based augmented alternative communication prototype will be designed with the active involvement of end users, caregivers and autism experts.

Objective

About 30% of children with autism are minimally verbal (MV), meaning they can communicate mainly through nonverbal vocalizations (i.e. vocalizations that do not have typical verbal content). Vocalizations often have self-consistent phonetic content and vary in tone, pitch, and duration depending on the individual's emotional state or intended communication. While vocalizations contain important affective and communicative information and are comprehensible by close caregivers, they are often poorly understood by those who do not know the communicator well. An improved understanding of nonverbal vocalizations could pave the way for a better understanding of the cognitive, social, and emotional mechanisms associated with MV children with autism. Moreover, it could lead to new therapeutic interventions for these subjects based on advanced voice-based technology for Augmented Alternative Communication (AAC), i.e. for communicating without using words.
This MSCA touches on the research fields of audio signal processing (in particular, children's vocalizations perception) and human-computer interaction (in particular, voice-based interfaces for speech therapy). It aims to advance the understanding of MV autistic children's vocalizations and exploit 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.

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2022-PF-01

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Coordinator

POLITECNICO DI MILANO
Net EU contribution

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.

€ 175 737,12
Address
PIAZZA LEONARDO DA VINCI 32
20133 Milano
Italy

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Region
Nord-Ovest Lombardia Milano
Activity type
Higher or Secondary Education Establishments
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Total cost

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