Story-Driven: Exploring the Impact of Providing Real-time Context Information on Automated Storytelling

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Stories have long captivated the human imagination with narratives that enrich our lives. Traditional storytelling methods are often static and not designed to adapt to the listener’s environment, which is full of dynamic changes. For instance, people often listen to stories in the form of podcasts or audiobooks while traveling in a car. Yet, conventional in-car storytelling systems do not embrace the adaptive potential of this space. The advent of generative AI is the key to creating content that is not just personalized but also responsive to the changing parameters of the environment. We introduce a novel system for interactive, real-time story narration that leverages environment and user context in correspondence with estimated arrival times to adjust the generated story continuously. Through two comprehensive real-world studies with a total of 30 participants in a vehicle, we assess the user experience, level of immersion, and perception of the environment provided by the prototype. Participants' feedback shows a significant improvement over traditional storytelling and highlights the importance of context information for generative storytelling systems.