Dao Si (AI Team Leader, JNG Studio of NUVERSE, NUVERSE)
Location: Room 2010, West Hall
Date: Tuesday, March 21
Time: 9:30 am - 10:30 am
All Access Pass, Summits Pass
Vault Recording: Video
Audience Level: All
Performance-driven narrative video games needed NPCs' performance to be realistic and depict a wide range of believable emotions. Accurate sentiment analysis and semantic understanding of the text can better help games' audio and animation content generation.
This session describes a novel system in 'Earth Revival', using GPT-3 to measure sentiment and extract semantic features, to automatically synthesize emotional voices and high-quality emotional, expressive full-body animations for talking NPCs. In this system, the speech synthesis system introduces paralinguistic elements to achieve realistic emotional expression, which can produce natural-sounding voices for final game releases or content updates. What's more, the automatic full-body animation generation model uses the multi-modal context of speech text, audio, and speaker identity to produce the arbitrary beat and semantic full-body animation together.
This system of GPT-3 powered text to lifelike speech and animation can significantly improve the narrative process and minimize time and cost.
Attendees will see how a system of GPT-3 powered text to lifelike speech and animation can significantly improve the narrative process and minimize time and cost. They can acquire the implementation detail of each component and improve the development efficiency.
This is for those who are interested in auto character animation generation, such as animators, technical animators, animation programmers, game designers, and more. Basic knowledge of machine learning techniques is preferred, but not required.