We trained a model to distinguish an extreme high arousal, unpleasant drink from regular drinks based on a range of implicit behavioral and physiological responses to naturalistic tasting. The trained model predicted arousal ratings of regular drinks, highlighting the possibility to estimate affective experience without having to rely on subjective ratings.
|Number of pages||8|
|Journal||IEEE transactions on affective computing|
|Early online date||19 Oct 2020|
|Publication status||Published - 2020|