A probabilistic, multidimensional model is described that accounts for sensory and hedonic ratings that are collected from the same experiment. The model combines a general recognition theory model of the sensory ratings with Coombs’ unfolding model of the hedonic ratings. The model uses sensory ratings to build a probabilistic, multidimensional representation of the sensory experiences elicited by exposure to each stimulus, and it also builds a similar representation of the hypothetical ideal stimulus in this same space. It accounts for hedonic ratings by measuring differences between the presented stimulus and the imagined ideal on each rated sensory dimension. Therefore, it provides precise estimates of the sensory qualities of the ideal on all rated sensory dimensions. The model is tested successfully against data from a new experiment.

描述了一个概率的多维模型，该模型解释了从同一实验中收集的感官和享乐评级。该模型将感官评级的一般识别理论模型与 Coombs 的享乐评级展开模型相结合。该模型使用感官评级来构建由暴露于每种刺激引起的感官体验的概率、多维表示，并且它还在同一空间中构建假设的理想刺激的类似表示。它通过测量每个额定感官维度上呈现的刺激和想象的理想之间的差异来解释享乐评级。因此，它提供了对所有额定感官维度上理想感官品质的精确估计。该模型已针对来自新实验的数据进行了成功测试。