Fan Zhang, Zhaohan Wang, Xin Lyu, Siyuan Zhao, Mengjian Li, Weidong Geng, Naye Ji, Hui Du, Fuxing Gao, Hao Wu, Shunman Li
Speech-driven gesture generation is an emerging field within virtual human creation. However, a significant challenge lies in accurately determining and processing the multitude of input features (such as acoustic, semantic, emotional, personality, and even subtle unknown features). Traditional approaches, reliant on various explicit feature inputs and complex multimodal processing, constrain the expressiveness of resulting gestures and limit their applicability. To address these challenges, we present Persona-Gestor, a novel end-to-end generative model designed to generate highly personalized 3D full-body gestures solely relying on raw speech audio...
April 24, 2024: IEEE Transactions on Visualization and Computer Graphics