From Words to Worlds: Transforming One-line Prompt into Immersive Multi-modal Digital Stories with Communicative LLM Agent

June 15, 2024 ยท Declared Dead ยท ๐Ÿ› arXiv.org

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Authors Samuel S. Sohn, Danrui Li, Sen Zhang, Che-Jui Chang, Mubbasir Kapadia arXiv ID 2406.10478 Category cs.CL: Computation & Language Cross-listed cs.AI, cs.GR Citations 3 Venue arXiv.org Last Checked 5 months ago
Abstract
Digital storytelling, essential in entertainment, education, and marketing, faces challenges in production scalability and flexibility. The StoryAgent framework, introduced in this paper, utilizes Large Language Models and generative tools to automate and refine digital storytelling. Employing a top-down story drafting and bottom-up asset generation approach, StoryAgent tackles key issues such as manual intervention, interactive scene orchestration, and narrative consistency. This framework enables efficient production of interactive and consistent narratives across multiple modalities, democratizing content creation and enhancing engagement. Our results demonstrate the framework's capability to produce coherent digital stories without reference videos, marking a significant advancement in automated digital storytelling.
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