Descripción del proyecto
Dar voz a los niños autistas mínimamente verbales
La comunicación es un aspecto básico de la vida. Sin embargo, esta constituye todo un reto para cerca del 30 % de los niños autistas mínimamente verbales. Estos niños utilizan sobre todo vocalizaciones no verbales para expresarse, que a menudo son malinterpretadas por quienes no tienen un vínculo estrecho con ellos. En el proyecto COMUTTI, que cuenta con el apoyo de las acciones Marie Skłodowska-Curie, se combinará el procesamiento de señales de audio y la interacción persona-ordenador para crear interfaces punteras basadas en la voz para logopedia. Se desarrollarán algoritmos de aprendizaje automático para clasificar estas vocalizaciones a partir de los conocimientos únicos de los cuidadores. Se diseñará un prototipo de comunicación alternativa aumentada basada en la voz con la participación activa de usuarios finales, cuidadores y expertos en autismo.
Objetivo
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.
Palabras clave
Programa(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Régimen de financiación
HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global FellowshipsCoordinador
20133 Milano
Italia