This paper investigates the innovative synthesis of procedurally generated visual and auditory content through the use of Artificial Intelligence (AI) Tools, specifically focusing on Generative Pre-Trained Transformer (GPT) networks. This research explores the process of procedurally generating an audiovisual representations of semantic context by generating images, artificially providing motion and generating corresponding multilayered sound. The process enables the generation of stopped-motion audiovisual representations of concepts. This approach not only highlights the capacity for Generative AI to produce cohesive and semantically rich audiovisual media but also delves into the interconnections between visual art, music, sonification, and computational creativity. By examining the synergy between generated imagery and corresponding soundscapes, this research paper aims to uncover new insights into the aesthetic and technical implications of the use of AI in art. This research embodies a direct application of AI technology across multiple disciplines creating intermodal media. Research findings propose a novel framework for understanding and advancing the use of AI in the creative processes, suggesting potential pathways for future interdisciplinary research and artistic expression. Through this work, this study contributes to the broader discourse on the role of AI in enhancing creative practices, offering perspectives on how various modes of semantic representation can be interleaved using state-of-the-art technology.
