Model Construction of “Kawaii Characters” Using Deep Learning

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In recent years, “kawaii” has been attracting attention as an affective value in manufacturing for various purposes. One example is the use of “kawaii characters” in marketing, PR and advertisement for several target groups especially young people. However, those “kawaii characters” have been designed and used intuitively without systematically evaluating their kawaii degree for target group. Since different target groups might have different preferences for kawaii characters, only intuitive design of kawaii characters might not fulfil their satisfaction and attract enough attention as expected. Therefore, this study proposes a systematic method to evaluate kawaii characters by constructing a model to classify kawaii characters with different physical attributes. To construct “kawaii character” dataset, we firstly prepared ten standard characters as images. Then, for each standard character, we prepared four different variations for each of these six physical attributes: eyebrows, eyes, mouth, facial (cheek) redness, clothing, and hair accessories. Next, we conducted a questionnaire to evaluate the kawaii degree of each kawaii character, and calculated it as “kawaii score”. Using the questionnaire results, we built a dataset containing a total of 120 images of kawaii characters and their corresponding kawaii scores. The dataset was used to construct a model using Deep Convolutional Neural Network (CNN) algorithm, which is a binary classification of kawaii characters into “kawaii” and “not-kawaii” group. Finally, we evaluated the classification performance of the model to confirm its performance for evaluating kawaii characters.

Original languageEnglish
Title of host publicationHuman-Computer Interaction. Theoretical Approaches and Design Methods - Thematic Area, HCI 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Proceedings
EditorsMasaaki Kurosu
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages9
ISBN (Print)9783031053108
Publication statusPublished - 2022
EventHuman Computer Interaction thematic area of the 24th International Conference on Human-Computer Interaction, HCII 2022 - Virtual, Online
Duration: 2022 Jun 262022 Jul 1

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13302 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceHuman Computer Interaction thematic area of the 24th International Conference on Human-Computer Interaction, HCII 2022
CityVirtual, Online


  • Character
  • Deep learning
  • Kawaii

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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