Search Results for author:
Found 6 papers, 1 papers with code
Investigating the Generalizability of Physiological Characteristics of Anxiety
To address this ambiguity, we evaluated the generalizability of physiological features that have been shown to be correlated with anxiety and stress to high-arousal emotions.
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.
Quality-Diversity Generative Sampling for Learning with Synthetic Data
QDGS is a model-agnostic framework that uses prompt guidance to optimize a quality objective across measures of diversity for synthetically generated data, without fine-tuning the generative model.
Evaluating Temporal Patterns in Applied Infant Affect Recognition
Next, we conducted an in-depth analysis of our best-performing models to evaluate how performance changed over time as the models encountered missing data and changing infant affect.
Introducing Representations of Facial Affect in Automated Multimodal Deception Detection
This approach achieved a higher AUC than existing automated machine learning approaches that used interpretable visual, vocal, and verbal features to detect deception in this dataset, but did not use facial affect.
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.
