Visualizing Individual Perceptual Differences Using Intuitive Word-Based Input.

Numerous studies have investigated the fundamental dimensions of human tactile perceptual space using a wide range of materials. Participants generally touch materials and quantitatively evaluate variations in tactile sensations for pairs of adjectives pertaining to the material properties, such as smooth-rough and soft-hard. Thus, observers evaluate their perceptual experiences one by one in terms of adjective pairs. We previously proposed an alternative method of qualitative evaluation of tactile sensations. Our system can automatically estimate ratings of fundamental tactile properties from single sound-symbolic words. We were able to construct a word-based perceptual space by collecting words that express tactile sensations and applying them to the system. However, to explore individual differences in perceptual spaces, different databases for converting words into ratings of adjective pairs are required for each individual. To address this, in the present study we created an application that can automatically generate an individualized perceptual space by moving only a few words in the initial word-based perceptual space. In addition, we evaluated the efficacy of the application by comparing the tactile perceptual space before and after use.