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Application of ChatGPT-Based Digital Human in Animation Creation

Author

Listed:
  • Chong Lan

    (School of Art and Design, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Yongsheng Wang

    (School of Art and Design, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Chengze Wang

    (School of Art and Design, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Shirong Song

    (School of Art and Design, Lanzhou Jiaotong University, Lanzhou 730070, China)

  • Zheng Gong

    (School of Art and Design, Lanzhou Jiaotong University, Lanzhou 730070, China)

Abstract

Traditional 3D animation creation involves a process of motion acquisition, dubbing, and mouth movement data binding for each character. To streamline animation creation, we propose combining artificial intelligence (AI) with a motion capture system. This integration aims to reduce the time, workload, and cost associated with animation creation. By utilizing AI and natural language processing, the characters can engage in independent learning, generating their own responses and interactions, thus moving away from the traditional method of creating digital characters with pre-defined behaviors. In this paper, we present an approach that employs a digital person’s animation environment. We utilized Unity plug-ins to drive the character’s mouth Blendshape, synchronize the character’s voice and mouth movements in Unity, and connect the digital person to an AI system. This integration enables AI-driven language interactions within animation production. Through experimentation, we evaluated the correctness of the natural language interaction of the digital human in the animated scene, the real-time synchronization of mouth movements, the potential for singularity in guiding users during digital human animation creation, and its ability to guide user interactions through its own thought process.

Suggested Citation

  • Chong Lan & Yongsheng Wang & Chengze Wang & Shirong Song & Zheng Gong, 2023. "Application of ChatGPT-Based Digital Human in Animation Creation," Future Internet, MDPI, vol. 15(9), pages 1-18, September.
    • Handle: RePEc:gam:jftint:v:15:y:2023:i:9:p:300-:d:1231661
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    References listed on IDEAS

    as
    1. Chris Stokel-Walker & Richard Van Noorden, 2023. "What ChatGPT and generative AI mean for science," Nature, Nature, vol. 614(7947), pages 214-216, February.
    2. Zhiyi Luo & Sirui Yan & Shuyun Luo, 2023. "Multitask Fine Tuning on Pretrained Language Model for Retrieval-Based Question Answering in Automotive Domain," Mathematics, MDPI, vol. 11(12), pages 1-13, June.
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