Year: 2025
Type: conference-paper
Abstract: Evaluating the quality of generated nonverbal behavior remains a major challenge in the development of generative models.While human evaluations are reliable, they are costly and impractical for large-scale or iterative optimization.In this work, we propose an objective evaluation framework based on aggregated ranks across multiple fidelity and diversity metrics, computed from both raw features and learned latent representations.Compared to existing works, our framework emphasizes consistency across multiple metrics, aiming to provide a more holistic assessment.
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4414959433