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Mental Image Directed Semantic Theory (MIDST) has already shown that each physical event concept (e.g., “carry”, “separate”) in natural language is characterized by a so-called “event pattern”, abstract pattern formed by the constituents of its referents. Therefore, people are assumed significantly aware of the event pattern involved when they cognize or recognize a physical event discerned with the others. Such event patterns are modeled as so-called “loci in attribute spaces” in MIDST. This is also the case for mental event concepts (e.g., “love”, “sympathize”). For example, a 5-dimensional attribute space can be provided for human emotion. This paper describes an approach toward a human mentality, so called Kansei, in order to provide robots with a function to measure peoples' emotions toward external things, focusing on human awareness in concept formation of affective words related to facial expressions of Buddhism statues.