Weakly-Supervised Emotion Transition Learning for Diverse 3D Co-speech Gesture Generation

arXiv:2311.17532v3 Announce Type: replace
Abstract: Generating vivid and emotional 3D co-speech gestures is crucial for virtual avatar animation in human-machine interaction applications. While the existing methods enable generating the gestures to follow a single emotion label, they overlook that long gesture sequence modeling with emotion transition is more practical in real scenes. In addition, the lack of large-scale available datasets with emotional transition speech and corresponding 3D human gestures also limits the addressing of this task. To fulfill this goal, …

arxiv cs.cv diverse emotion speech transition type weakly-supervised