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How Can Large Language Models Enable Better Socially Assistive Human-Robot Interaction: A Brief Survey
Socially assistive robots (SARs) have shown great success in providing personalized cognitive-affective support for user populations with special needs such as older adults, children with autism spectrum disorder (ASD), and individuals with mental health challenges.
Evaluating and Personalizing User-Perceived Quality of Text-to-Speech Voices for Delivering Mindfulness Meditation with Different Physical Embodiments
Building on findings from Phase 1, in Phase 2, an in-person within-subject study (N=94), we used a novel framework we developed for personalizing TTS voices based on user preferences, and evaluated user-perceived quality compared to best-rated non-personalized voices from Phase 1.
Build Your Own Robot Friend: An Open-Source Learning Module for Accessible and Engaging AI Education
We hope that this work will contribute toward accessible and engaging AI education in human-AI interaction for college and high school students.
MaSS: Multi-attribute Selective Suppression
The recent rapid advances in machine learning technologies largely depend on the vast richness of data available today, in terms of both the quantity and the rich content contained within.
Modeling Engagement in Long-Term, In-Home Socially Assistive Robot Interventions for Children with Autism Spectrum Disorders
This work applies supervised machine learning algorithms to model user engagement in the context of long-term, in-home SAR interventions for children with ASD.
