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Session Name:

Machine Learning Summit: GPT-3 Powered Text to Lifelike Speech and Animation for NPCs

Overview:

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.

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