AromaGen: Interactive Generation of Rich Olfactory Experiences with Multimodal Language Models
Smell's connections with food, memory, and social experience have motivated researchers to bring olfaction into interactive systems. Multimodal AI opens new possibilities for generating smells from natural language, yet it remains unclear whether pretrained models encode sufficient olfactory knowledge to translate language into perceptible compositions. We present AromaGen, an AI-powered 12-channel wearable olfactory system that maps free-form natural-language descriptions to 12 base odorants selected to cover a semantically derived olfactory space, while supporting iterative refinement through natural-language feedback. In a between-subjects study (N=60) across 50 real-world benchmark sm...
| Authors | Awu Chen, Silang Wang, Yunge Wen et al. |
|---|---|
| Primary category | cs.HC |
| Published | 2 April 2026 |
| Last updated at source | 9 October 2026 |
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