Abstract: This paper introduces an AI-based story generation system using Recurrent Neural Networks (RNNs) to create structured stories, such as dialogues, emotions, and cinematic scene descriptions. The proposed model employs a deep learning scriptwriting automation process with the integration of AI- enabled visuals, voice acting, and cinematic editing to create a fully automated storytelling process. The system is intended to boost creativity through the input of story prompts, which the AI transforms into well-structured stories. Using large-scale structured movie script datasets, the AI acquires patterns of storytelling, such as character interactions, scene changes, and narrative pacing. The use of Stable Diffusion for visual generation and ElevenLabs for voice synthesis further enriches the story- telling experience, creating a multimedia-rich output. The use of MoviePy also provides for audio and video integration without any gaps, creating professional-quality cinematic presentations. The ultimate aim of this system is to extend the limits of AI- assisted creativity, offering a tool for writers, filmmakers, and content creators to venture into new horizons in automated storytelling.
Index Terms: Artificial Intelligence, Recurrent Neural Net- works, Deep Learning, Story Generation, Automated Scriptwrit- ing, Natural Language Processing, Cinematic Scene Generation, AI-driven Storytelling, Voice Synthesis, Visual Generation, Text- to-Speech, Neural Storyteller, Machine Learning in Creativity, Reinforcement Learning in Storytelling.
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DOI:
10.17148/IJARCCE.2025.14432
