AI-Driven Conversational Storytelling with Humans in Natural Language

人工智能驱动的自然语言对话式讲故事-讲故事长期以来一直是人类社会和娱乐的核心部分，在历史上有多种形式。然而，传统形式的讲故事通常涉及被动的观众体验，并且对更具互动性和吸引力的讲故事体验的需求不断增长。互动是学校和娱乐体验的重要组成部分，但它必须与叙述的完整性仔细平衡。这在对话式人工智能和机器人技术的背景下尤为重要，因为过度的互动会破坏故事，而互动不足会导致观众脱离。因此，叙事互动是对话式人工智能领域的一个关键问题。然而，实现人机交互和引人入胜的叙事之间的平衡需要大量的研究，设计和培训工作。在这个项目中，我建议探索会话式讲故事和机器/深度学习的当前技术水平，并开发一个新的框架/模型，通过实时讲述和解释来自不同模式的事实来支持主动学习能力，例如基于文本的数据，图像，视频和物理演示。我还将研究多角色对话对观众的影响。这些知识有可能解决对话人工智能和人机交互中最大的挑战之一，并为交互式和引人入胜的叙事体验提供关键解决方案[1]。该项目还提出研究然后创建一个新的框架，用于创建交互式叙事体验，通过使用大型语言模型（LLM），如GPT，实时有效地吸引和教育用户。3和计算机视觉技术，如CNN和LSTM。该项目的目标是创建一个响应系统，能够实时理解和响应用户的手势和情绪，以适应叙述。该系统将被设计用于各种应用，如讲故事，教育和娱乐。

AI-Driven Conversational Storytelling with Humans in Natural Language - Storytelling has long been a central part of human society and entertainment and has taken many forms throughout history. However, traditional forms of storytelling often involve passive viewer experiences, and there is a growing demand for more interactive and engaging storytelling experiences. Interactivity is an essential part of the school and entertainment experience, but it must be carefully balanced with the integrity of the narrative. This is particularly important in the context of conversational AI and robotics, where excessive interaction can disrupt the story and insufficient interaction can lead to audience disengagement.Narrative interaction is therefore a crucial issue in the field of conversational AI. However, achieving a balance between human-machine interaction and engaging narrative requires significant study, design and training efforts. In this project, I propose to explore the current state of the art in conversational storytelling, and machine/deep learning, and develop a new framework/model to support active learning capabilities through real-time telling and interpreting facts from different modes such as text-based data, images, video, and physical presentations. I will also examine the impact of multi-character dialogue on the audience. This knowledge has the potential to address one of the biggest challenges in conversational AI and human-machine interactions and provide a key solution for interactive and engaging narrative experiences [1].This project also proposes the research then creation of a new framework for creating interactive narrative experiences that effectively engage and educate users in real-time by using a large language model (LLM) such as GPT-3 and computer vision techniques such as CNNs and LSTMs. The goal of this project is to create a responsive system that is capable of understanding and responding to user gestures and emotions in real-time in order to adapt the narrative. The system will be designed to be used in a variety of applications such as storytelling, education, and entertainment.