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.

翻译：数字叙事在娱乐、教育和营销领域至关重要，但其生产可扩展性与灵活性面临挑战。本文提出的StoryAgent框架利用大语言模型与生成式工具，实现数字叙事的自动化与精细化。通过采用自上而下的故事草拟与自下而上的资产生成方法，StoryAgent解决了人工干预、交互式场景编排及叙事一致性等关键问题。该框架能够高效生产跨多模态的交互式且连贯的叙事内容，从而普及内容创作并提升参与度。我们的实验结果表明，该框架无需参考视频即可生成连贯的数字故事，标志着自动化数字叙事领域的重大进展。