Yunge Wen, Awu Chen, Jianing Yu, Jas Brooks, Hiroshi Ishii, Paul Pu Liang

Researchers at MIT and collaborators have developed AromaGen, an AI-powered wearable that generates custom scents from text or image inputs using a multimodal language model. The system maps semantic descriptions to mixtures of 12 base odorants released through a neck-worn dispenser, and users can refine results through natural language feedback. In a 26-person study, AromaGen matched human-composed aromas in zero-shot generation and significantly outperformed them after iterative refinement, achieving median similarity scores of 8/10 to real food scents while reducing perceived artificiality.