no code implementations • 1 Apr 2024 • Zhonghao Shi, Ellen Landrum, Amy O' Connell, Mina Kian, Leticia Pinto-Alva, Kaleen Shrestha, Xiaoyuan Zhu, Maja J Matarić
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.
no code implementations • 7 Jan 2024 • Zhonghao Shi, Han Chen, Anna-Maria Velentza, SiQi Liu, Nathaniel Dennler, Allison O'Connell, Maja Matarić
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.
no code implementations • 6 Jan 2024 • Zhonghao Shi, Allison O'Connell, Zongjian Li, SiQi Liu, Jennifer Ayissi, Guy Hoffman, Mohammad Soleymani, Maja J. Matarić
We hope that this work will contribute toward accessible and engaging AI education in human-AI interaction for college and high school students.
no code implementations • 18 Oct 2022 • Chun-Fu Chen, Shaohan Hu, Zhonghao Shi, Prateek Gulati, Bill Moriarty, Marco Pistoia, Vincenzo Piuri, Pierangela Samarati
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.
no code implementations • 6 Feb 2020 • Shomik Jain, Balasubramanian Thiagarajan, Zhonghao Shi, Caitlyn Clabaugh, Maja J. Matarić
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.