A Generative Audio-Visual Prosodic Model for Virtual Actors.

Abstract

An important problem in computer animation of virtual characters is the expression of complex mental states during conversation using the coordinated prosody of voice, rhythm, facial expressions, and head and gaze motion. In this work, the authors propose an expressive conversion method for generating natural speech and facial animation in a variety of recognizable attitudes, using neutral speech and animation as input. Their method works by automatically learning prototypical prosodic contours at the sentence level from an original dataset of dramatic attitudes.