TED-culture: culturally inclusive co-speech gesture generation for embodied social agents.

ABSTRACT: Generating natural and expressive co-speech gestures for conversational virtual agents and social robots is crucial for enhancing their acceptability and usability in real-world contexts. However, this task is complicated by strong cultural and linguistic influences on gesture patterns, exacerbated by the limited availability of cross-cultural co-speech gesture datasets. To address this gap, we introduce the TED-Culture Dataset, a novel dataset derived from TED talks, designed to enable cross-cultural gesture generation based on linguistic cues. We propose a generative model based on the Stable Diffusion architecture, which we evaluate on both the TED-Expressive Dataset and the TED-Culture Dataset. The model is further implemented on the NAO robot to assess real-time performance. Our model

SUBMITTER: Shen Y 

PROVIDER: S-EPMC12011587 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature