TEXT TO MUSIC CONVERSION VIA INTERMEDIATE IMAGE REPRESENTATION: A CROSS-MODAL AI APPROACH

Converting text to music represents a novel intersection of language processing, visual representation, and musical creativity within the field of artificial intelligence.This paper explores a two-step approach to this challenge, first generating images from textual descriptions using state-of-the-art text-to-image models, and then converting these images into music through advanced image-to-music algorithms.The methodology leverages the strengths of cross-modal AI to translate semantic meaning from text into the auditory domain, offering a unique pathway for creative expression.The results highlight both the potential and limitations of this approach, paving the way for further research in multimodal generative models.