A multimodal symphony: integrating taste and sound through generative AI - Spanio, Matteo; Zampini, Massimiliano; Rodà, Antonio; Pierucci, Franco (Frontiers in Computer Science, 2025)
In recent decades, neuroscientific and psychological research has identified direct relationships between taste and auditory perception. This article explores multimodal generative models capable of converting taste information into music, building on this foundational research. We provide a brief review of the state of the art in this field, highlighting key findings and methodologies. We present an experiment in which a fine-tuned version of a generative music model (MusicGEN) is used to generate music based on detailed taste descriptions provided for each musical piece. The results are promising: according to the participants' evaluations (n = 111), the fine-tuned model produces music that more coherently reflects the input taste descriptions compared to the non-fine-tuned model. This study represents a significant step toward understanding and developing embodied interactions between AI, sound, and taste, opening new possibilities in the field of generative AI.