Visual artists can consult a digital color wheel to test relationships between different shades. Audio engineers can alter soundwave frequencies to create complex tones and harmonies. But no digital tools exist that can predict how people will perceive the blend of scents wafting from a steaming cup of coffee or a freshly baked apple pie. In new Yale-led study, researchers developed a machine learning method to accurately predict how people perceive different scent combinations. The advance is an important step toward creating a quantitative framework for understanding our perceptions of complex odors, which the researchers say could someday lead to applications relevant to human health.
Is it possible to measure how people perceive odors?Unlike vision, where the trichromatic theory helps explain how combinations of primary colors enrich our visual world, there is no quantifiable framework for mapping our perceptions of odors. A new Yale-led study uses machine learning to predict how people will perceive complex odors — an important step toward digitally mapping scent perceptions. What are the potential benefits of digitally mapping perceptions of smell? Potential applications could be relevant to human health. Many health conditions, such as Parkinson’s and cancer, have been reported to have odor signatures. There could be technology years from now that can monitor your smell and alert you to any changes that might require additional screening.
