Abstract
Language and emotions play an important role in affective computing and advancement of artificial intelligence. Sound-symbolic words (SSWs) have become increasingly important for meaningful descriptions of perceptual experiences as a detailed and reliable vocabulary. In this research, we constructed a system for quantifying texture/taste impressions expressed by SSWs. This system decomposes input SSW into phoneme elements and refers to the category quantity of each phoneme element for each adjective scale referring to a quantitative rating database. Then, the system displays the evaluation values calculated by impression-rating predictive model. We anticipate that this system will be able to support food development and recommendation of food name which expresses the impression of goods.
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Acknowledgments
This work was supported by Grant-in-Aid for Scientific Research (A) Grant Number 15H01720), a Grant-in-Aid for Scientific Research on Innovative Areas “Shitsukan” (Grant Number 23135510 and 25135713), and JSPS KAKENHI Grant Number 15H05922 (Grant-in-Aid for Scientific Research on Innovative Areas “Innovative SHITSUKSAN Science and Technology”) from MEXT, Japan.
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Inazumi, T., Kwon, J., Suzuki, K., Sakamoto, M. (2019). Affective Taste Evaluation System Using Sound Symbolic Words. In: Fukuda, S. (eds) Advances in Affective and Pleasurable Design. AHFE 2018. Advances in Intelligent Systems and Computing, vol 774. Springer, Cham. https://doi.org/10.1007/978-3-319-94944-4_40
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DOI: https://doi.org/10.1007/978-3-319-94944-4_40
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