admin – KISLAB-感性情報システム研究室

2026

admin — Fri, 20 Mar 2026 08:25:33 +0000

Faculty Staff

Masataka Tokumaru (Professor, Principal Investigator)

Emmanuel Ayedoun (Associate Professor)

Personal website

Master’s course, 2nd year (M2)

Arata Kawashima

Yuto Tsubouchi

Hayato Nakamura

Sae Yamanaka

Master’s course, 1st year (M1)

Taiga Ikushima

Yuzuto Okahashi

Rina Sakagami

Ryusei Naka

Yuto Maeda

Reo Yamatsuka

Bachelor course, senior (B4)

Yuta Inoue

Ichiyo Komatsu

Itsuki Sedooka

Masashi Nishimura

Iori Hasegawa

Ryoto Machida

Gao Yanxin

Honoka Yamamura

2025

admin — Sat, 24 May 2025 08:42:40 +0000

Faculty Staff

Masataka Tokumaru (Professor, Principal Investigator)

Emmanuel Ayedoun (Associate Professor)

Personal website

Master’s course, 2nd year (M2)

Ryusei Azuma

Keishi Oya

Seiya Sakaguchi

Yuma Shimosaka

Sora Yamamoto

Master’s course, 1st year (M1)

Arata Kawashima

Yuto Tsubouchi

Hayato Nakamura

Sae Yamanaka

Bachelor course, senior (B4)

Taiga Ikushima

Yuzuto Okahashi

Rina Sakagami

Kakeru Takeuchi

Ryusei Naka

Ayumi Hayashi

Renya Fujii

Yuto Maeda

Tomonari Kawano

Han Yufeng

2024

admin — Sat, 24 May 2025 07:57:03 +0000

Faculty Staff

Masataka Tokumaru (Professor, Principal Investigator)

Emmanuel Ayedoun (Assistant Professor)

Personal website

Master’s course, 2nd year (M2)

Akira Inaba

Yuri Kanazawa

Tetsuaki Togo

Yoshiki Tominaga

Kaito Nagayasu

Kazuki Matsumoto

Ryoto Mikawa

Master’s course, 1st year (M1)

Ryusei Azuma

Keishi Oya

Seiya Sakaguchi

Yuma Shimosaka

Sora Yamamoto

Bachelor course, senior (B4)

Maho Asano

Haruka Kadosugi

Arata Kawashima

Yuto Tsubouchi

Hayato Nakamura

Takuto Nishibata

Tatsuya Yamashita

Sae Yamanaka

Reo Yamatsuka

2023

admin — Sat, 24 May 2025 06:55:50 +0000

Faculty Staff

Masataka Tokumaru (Professor, Principal Investigator)

Emmanuel Ayedoun (Assistant Professor)

Personal website

Master course, 2nd year (M2)

Misaki Endo

Rikuto Kobayashi

Yuki Koike

Yusuke Sakabe

Fuma Yamamoto

Yuya Tsubokura

Master’s course, 1st year (M1)

Akira Inaba

Yuri Kanazawa

Tetsuaki Togo

Yoshiki Tominaga

Kaito Nagayasu

Kazuki Matsumoto

Ryoto Mikawa

Bachelor course, senior (B4)

Ryusei Azuma

Keishi Oya

Seiya Sakaguchi

Yuma Shimosaka

Shun Kato

Sora Yamamoto

Toji Morita

Chengwen Ni

KISLAB News

admin — Fri, 29 Nov 2024 08:20:55 +0000

2025.11.30~12.6 Conference Presentation: ICCE@India

2025.11.6~11.9 Conference Presentation: ISIS@Korea

2025.8.25~9.17 Welcome to Karina & Lin

2025.8.9~10 Seminar Trip@Hukutiyama

2025.6.30~7.31 Welcome to Lee & Michał

2024.8.1~2 Seminar Trip @Shiga Prefecture

2024.6.7 Welcome to Gotj & Pajaree

2023.8.3~4 Seminar Trip @Kyōtanba

Key Papers

admin — Thu, 28 Nov 2024 09:24:50 +0000

Journal Papers

*Collaborative researcher

Keishi Ohya, Emmanuel Ayedoun, Masataka Tokumaru, “Prompt-Optimized Music Generation: A User Feedback-Adaptive AI System”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.30, No.2, pp.579-588, 2026-03.

Yoshiki Tominaga, Emmanuel Ayedoun, Masataka Tokumaru, “Advertising Statement Optimization System based on Consumer Type Classification”, International Journal of Affective Engineering, Vol.25, No.1, pp.119-136, 2026-01.

Satoko Inoue, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru, “Leveraging Interactive Evolutionary Computation to Induce Serendipity in Informal Learning”, Multimodal Technologies and Interaction, Vol.8, No.11:103, 2024-11. https://doi.org/10.3390/mti8110103

Yusuke Sakabe, Emmanuel Ayedoun, Masataka Tokumaru, “Leveraging IEC and Others’ Viewpoints Presentation to Support Creative Thinking”, International Journal of Affective Engineering, Vol.23, No.2, pp.157-168, 2024-07.

Emmanuel Ayedoun, Marina Goto, Masataka Tokumaru, “Swarm Intelligence Inspired Approach for Dynamic Tracking of Members’ Interests in Online Discussion Groups”, International Journal of Affective Engineering, Vol.22, No. 2,ol.22, No. 2, 2023-05. First Online: https://doi.org/10.5057/ijae.IJAE-D-22-00012

小林陸門，アイエドゥンエマヌエル，徳丸正孝，“運動の継続意欲向上を促すリズム補正システム”，日本知能情報ファジィ学会誌知能と情報，Vol.35, No.2, pp.501-505, 2023-05.

*Yotaro Fuse, Biina Ashida, Emmanuel Ayedoun, Masataka Tokumaru, “Unleashing Fairness: How a Group Norm-Aware Agent Shakes Up the Ultimatum Game”, IEEE Access, Vol. 11, pp. 36727-36740, 2023-04.

*芦田淳，徳丸正孝，小尻智子，“質問応答手法を用いたメッセージ伝達のための物語構造導出支援システム”，教育システム情報学会誌，Vol.40, No.2, pp.155-160, 2023-04.

*Yotaro Fuse, Biina Ashida, Emmanuel Ayedoun, Masataka Tokumaru, “Unleashing Fairness: How a Group Norm-Aware Agent Shakes Up the Ultimatum Game”, IEEE Access, Vol. 11, pp. 36727-36740, 2023-04.

*Hiroshi Takenouchi, Masataka Tokumaru, “Interactive Evolutionary Computation with Artificial Bee Colony Method for Multimodal Preferences Retrieval”, International Journal of Affective Engineering, Vol.22, No.1, pp.1-10, 2023-01.

Emmanuel Ayedoun, Masataka Tokumaru, “Towards Emotionally Expressive Virtual Human Agents to Foster L2 Production: insights from a preliminary Woz experiment”, Multimodal Technol. Interact. Journal Vol.6, No.9, pp.77-91, 2022-09. https://doi.org/10.3390/mti6090077, 2022-09.

Yotaro Fuse, Emmanuel Ayedoun, Masataka Tokumaru, “Group Norm-Aware Robot Adaptively Maintains Suitable Interpersonal Distance in Human–Robot Group” International Journal of Affective Engineering, Vol.21, No.3, pp. 191-201, 2022-07. https://doi.org/10.5057/ijae.TJSKE-D-21-00078, 2022-07.

*Yuka Nishimura, Hiroshi Takenouchi, Masataka Tokumaru, “Extracting Preference Rules Using Kansei Retrieval Agents with Fuzzy Inference”, International Journal of Affective Engineering, Vol.21, No.3, pp.181-190, 2022-07.

*Hiroshi Takenouchi, Masataka Tokumaru, “Character Design Generation System Using Multiple Users’ Gaze Information”, IEICE TRANSACTIONS on Information and Systems, Vol.E104-D, No.9, pp.1459-1466, 2021-09.

*竹之内宏，徳丸正孝，“対話型進化計算システムにおける一対比較評価の有用性”，情報処理，Vol.62, No.5, pp.d80-d97, 2021-04.（招待論文）

井上聡子，徳丸正孝，“セレンディピティ誘発に着目した情報推薦システム”，日本知能情報ファジィ学会誌知能と情報，Vol.33, No.1, pp.501-505，2021-02．（ショートノート）

*Atsushi Ashida, Masataka Tokumaru, Tomoko Kojiri, “Characters’ Emotion Design Support System for Writing Novels Based on Story Arcs of Target Readers”, Information and Technology in Education and Learning, Vol. 1, Issue 1, Pages Reg-p005, 2021-01.

Naoki Kaji, Hiroshi Takenouchi, Masataka Tokumaru, “Performance Evaluation of T-Shirt Image Generation System Considering User’s Preference”, International Journal of Affective Engineering, Vol.19, No.4, pp.283-291, 2020-12.

Yotaro Fuse, Masataka Tokumaru, “Navigation Model for a Robot as a Human Group Member to Adapt to Changing Conditions of Personal Space”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 24, No. 5, pp. 621-629, 2020-09.

Yotaro Fuse, Masataka Tokumaru, “Social Influence of Group Norms Developed by Human-Robot Groups”, IEEE Access, Vol.8, pp.56081-56091, 2020-03.

早川元基，徳丸正孝，“外部環境を考慮したロボットの個性形成モデル”，日本知能情報ファジィ学会論文誌知能と情報, Vol.32, No.1, pp.550-555, 2020-02.（ショートノート）

Yotaro Fuse, Hiroshi Takenouchi, Masataka Tokumaru, “A Robot in a Human–Robot Group Learns Group Norms and Makes Decisions through Indirect Mutual Interaction with Humans,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.24, No.1, pp.169-178, 2020-01.

*Hiroshi Takenouchi, Masataka Tokumaru, “Interactive Evolutionary Computation System with User Gaze Information”, International Journal of Affective Engineering, Vol.18, No.3, pp.109-116, 2019-07.

Yotaro Fuse，Hiroshi Takenouchi, Masataka Tokumaru, “A Robot Model That Obeys a Norm of a Human Group by Participating in the Group and Interacting with Its Members”, IEICE TRANSACTIONS on Information and Systems, VOL.E102-D, No.1, pp.185-194, 2019-01.

*藤﨑美夏, 竹之内宏, 徳丸正孝, “複数ユーザの視線情報を用いた対話型進化計算システム”, 日本知能情報ファジィ学会論文誌知能と情報, Vol.30, No.4, pp.613-622, 2018-08.

Yuta Hayashi, Ryouta Oku, Hiroshi Takenouchi, Masataka Tokuamaru, “Healthy Eating Habits Support System Considering User Taste Preferences and Nutritional Balance”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.22, No.1, pp.97-103, 2018-01.

*Hiroshi Takenouchi, Masataka Tokuamaru, “Kansei Retrieval Agent Model with Fuzzy Reasoning”, International Journal of Fuzzy Systems, Vol.19, Issue.6, pp.1803-1811, 2017-12.

太田茂，竹之内宏，徳丸正孝,”深層ニューラルネットワークによる特徴抽出を用いた衣服の感性検索”, 日本感性工学会論文誌, Vol.16, No.3, pp.277-283, 2017-06.

坂井将之，竹之内宏，徳丸正孝，“デジタルサイネージを用いた複数のユーザの投票によるデザイン生成支援システム”，日本感性工学会論文誌，Vol.15, No.4, pp.503-511, 2016-08．

Shoji Iguchi, Hiroshi Takenouchi, Masataka Tokumaru, “Effectiveness of a Sympathy Expression Model for the Bystander Robot”, International Journal of Affective Engineering, Vol.15, No.3, pp.223-230, 2016-07.

徳丸正孝，“感性データマイニング −製品の印象分析−”，精密工学会誌，Vol.82, No.1, pp.43-46, 2016-01．

Takaki Urai, Masataka Tokuamaru, “User Kansei Clothing Image Retrieval System”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.18, No.6 pp. 1044-1052, 2014-11.

末次峻也，片山尋貴，徳丸正孝，“並列GAによる感性データ解析，日本知能情報ファジィ学会誌「知能と情報」，Vol.25, No.6, pp.924-934, 2013-12．

Hiroshi Takenouchi, Masataka Tokumaru, Noriaki Muranaka, “Tournament-style Evaluation using Kansei Evaluation”, International Journal of Affective Engineering, Vol.12, No.3, pp.395-407, 2013-09.

Miho Harata, Masataka Tokumaru, “An emotion generation model with growth functions for robots”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.17, No.2, pp.335-342, 2013-03.

Yuta Tokumi, Junki Hakamata, Masataka Tokumaru “Development of a nutritional management system for a healthy eating habits support system”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.17, No.2, pp.324-334, 2013-03.

Hiroshi Takenouchi, Masataka Tokumaru, Noriaki Muranaka, “Interactive Evolutionary Computation Using a Tabu Search Algorithm”, IEICE TRANSACTIONS on Information and Systems, Vol.E96-D, No.3, pp.673-680, 2013-03.

Hiroshi Takenouchi, Masataka Tokumaru, Noriaki Muranaka, “Tournament Evaluation System Applying Win-Lose Result Presumption Considering Kansei Evaluation by Multiple People”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.16, No.3, pp.453-461, 2012-05.

袴田隼毅，徳美雄大，徳丸正孝，“対話型進化計算を用いたレコメンドシステムフレームワーク”，日本感性工学会論文誌，Vol.11, No.2, pp.281-288, 2012-03.

奥中大地，徳丸正孝，“ニューラルネットワークを用いた感性検索モデル”，日本感性工学会論文誌，Vol.11, No.2, pp.331-338, 2012-03.

竹之内宏，徳丸正孝，村中徳明，“２点嗜好法を適用した複数参加型トーナメント方式を用いた対話型遺伝的アルゴリズム”，日本知能情報ファジィ学会誌知能と情報, Vol.23, No.1, pp.38-53, 2011-02.

Hiroshi Takenouchi, Masataka Tokumaru, Noriaki Muranaka, “Tournament Evaluation System Considering Multiple People’s Kansei Evaluation”, Journal of Kansei Engineering International, Vol.9, No.2, pp.43-50, 2010-06.

Masataka Tokumaru, Noriaki Muranaka, “Product-Impression Analysis Using Fuzzy C4.5 Decision Tree”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.13, No.6, pp.731-737, 2009-11.

徳丸正孝，村中徳明，“対話型進化計算による感性検索エージェントの最適化”，日本感性工学会感性工学研究論文集，Vol.8, No.3, pp.885-892, 2009-02．

徳丸正孝，村中徳明，“配色のイメージに関する感性を持ったロボットの開発”，日本感性工学会感性工学研究論文集，Vol.7, No.4, pp.741-748, 2008-06．

井上康司，徳丸正孝，村中徳明，“ニューラルネットを用いた感性ロボットの自発的行動と欲求制御”，日本感性工学会感性工学研究論文集，Vol.7, No.4, pp.733-740, 2008-06．

徳丸正孝，村中徳明，今西茂，“「記憶と忘却」を繰り返し発想し続けるシステム　－記憶パターン更新型カオスニューラルネットワークと作曲システムへの応用－”，日本知能情報ファジィ学会誌知能と情報，Vol.19, No.3, pp.299-312, 2007-06.

徳丸正孝，村中徳明，“感性情報の分析を目的としたファジィ決定木の構成”，電子情報通信学会論文誌D，Vol.J90-D, No.5, pp.1305-1307, 2007-05.

徳丸正孝，村中徳明，今西茂，“ファジィ手法による色彩調和の定量的評価”，日本知能情報ファジィ学会誌知能と情報，Vol.19, No.1, pp.57-68, 2007-02.

徳丸正孝，大竹孝昌，村中徳明，今西茂，“音楽で「遊ぶ」ことを目的とした作曲システムの構築に関する検討”，日本感性工学会感性工学研究論文集，Vol.5, No.4, pp.45-52, 2005-08．

徳丸正孝，平岡信人，山下一美，長尾裕史，鳴尾丈司，村中徳明，今西茂，“GMDHとニューラルネットワークによる製品の使いやすさと魅力の解析”，日本感性工学会感性工学研究論文集，Vol.5, No.3, pp.111-118, 2005-05.

徳丸正孝, 平岡信人, 山下一美（大阪市立大学名誉教授）, 長尾裕史, 鳴尾丈司, 佐藤文宣（ミズノ（株））, 村中徳明, 今西茂, “決定木による製品の使いやすさと魅力の解析 -ゴルフクラブの打ちやすさと好みに関するルールの抽出-”, 日本感性工学会誌感性工学研究論文集, Vol.2, No.2, pp.65-72, 2002.8.

徳丸正孝，村中徳明，今西茂, “感性インタフェースを用いた対話型編曲システム”, 日本感性工学会誌感性工学研究論文集，Vol.1, No.2, pp.73-80, 2001.8.

徳丸正孝，村中徳明，今西茂, “配色イメージ判定における個人差を考慮したシステム構築の試み”, 電子情報通信学会論文誌, Vol.J84-D-II, No.4, pp.688-698, 2001.4.

徳丸正孝，山下一美，“ファジー推論を用いた配色のイメージ判定システムの構築”，電子情報通信学会論文誌 D-II，Vol.J38-D-II, No.2, pp.680 -689, 2000.2.

徳丸正孝，山下一美，村中徳明，今西　茂，“パートナー型編曲システム“HASCAP”における編曲者の主観的曖昧性を含む音楽的知識の導入について”，日本ファジィ学会誌，Vol.10, No.5, pp.876-887, 1998.5.

Intl Conf. Papers

*Collaborative researcher

[137]Arata Kawashima, Emmanuel Ayedoun, Masataka Tokumaru, “Multi-Dialogue Agents for Collaborative Learning Support Through Adaptive Opinion Integration”, International Conference on Computers in Education 2025, 2025-12 (Chennai, India).

[136]Yuto Tsubouchi, Emmanuel Ayedoun, Masataka Tokumaru, “IEC Driven Guitar Etude Optimization System Considering Learner Preferences and Skills”, International Conference on Computers in Education 2025, 2025-12 (Chennai, India).

[135]Hayato Nakamura, Emmanuel Ayedoun, Masataka Tokumaru, “Exercise Support System Using Audience Robot Behavior”, The 26th International Symposium on Advanced Intelligent Systems, FA7-4, pp.329-332, 2025-11 (Cheongju, Korea).

[134]Sae Yamanaka, Emmanuel Ayedoun, Masataka Tokumaru, “A Cognitive Model that Derives Multiple Interpretations from a Single Fact for Narrative Therapy Applications”, The 26th International Symposium on Advanced Intelligent Systems, FA7-5, pp.333-336, 2025-11 (Cheongju, Korea).

[133]Hiroshi Takenouch, Haru Takara, Masataka Tokumaru, “Interactive Evolutionary Computation with Prompts Optimization Including Sensitivity Impressions in Image Generative AI”, The 26th International Symposium on Advanced Intelligent Systems, SM4-1, pp.480-483, 2025-11 (Cheongju, Korea).

[132]Akira Inaba, Emmanuel Ayedoun, Masataka Tokumaru, “Adaptive Psychological Distance in Japanese Spoken Human-Agent Dialogue: A Politeness-Based Management Model”, Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology, pp.324-329, 2025-05 (Bilbao, Spain).

[131]Yotaro Fuse, Emmanuel Ayedoun, Masataka Tokumaru, “Group Norm-Aware Agents in Human Ultimatum Games: Impact and Implications”, International Conference on Human-Computer Interaction, Cham: Springer Nature Switzerland, pp.207-221, 2025-06 (Gothenburg, Sweden).

[130]Hiroshi Takenouchi, Mio Nakajima, Masataka Tokumaru, “User-Preference Rule Generation in Automatic Virtual Makeup System”, International Conference on Human-Computer Interaction, Cham: Springer Nature Switzerland, pp. 377-387, 2025-06 (Gothenburg, Sweden).

[129]Ryusei Azuma, Emmanuel Ayedoun, Masataka Tokumaru, “Exploring the Benefits of Strategic Hesitations in Language Learning Robots”, Proceedings of the 32nd International Conference on Computers in Education (ICCE2024), Volume II, pp.592-598, 2024-11 (Manila, Philippines).

[128]Yuma Shimosaka, Emmanuel Ayedoun, Masataka Tokumaru, “Optimization of Non-Verbal Information for English Conversation Agents Using Interactive Evolutionary Computation”, Proceedings of the 32nd International Conference on Computers in Education (ICCE2024), Volume II, pp.585-591, 2024-11 (Manila, Philippines).

[127]Yusuke Sakabe, Emmanuel Ayedoun, Masataka Tokumaru, “MESHing Minds: Bridging the Gap Between Creativity and IoT Programming Through Collaborative Mixed Reality”, Proceedings of the 32nd International Conference on Computers in Education (ICCE2024), Volume I, pp.145-154, 2024-11 (Manila, Philippines).Best Student Paper Award

[126]Hiroshi Takenouchi, Brahim Benaissa, Masataka Tokumaru, “New Interactive Evolutionary Algorithm”, 10th International Conference on Kansei Engineering and Emotion Research 2022 (KEER2024), PBC-0002, pp.819-822, 2024-11 (Taichung, Taiwan).

[125]Yoshiki Tominaga, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru, “POP Advertisement Generate System based on Regulatory Focus Theory and IEC”, 10th International Conference on Kansei Engineering and Emotion Research 2022 (KEER2024), OAA-0034, pp.231-242, 2024-11 (Taichung, Taiwan).Best Conference Paper Award

[124]Tetsuaki Togo, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru, “Product Recommendation System That Promotes Selection Using Dominance Structuring Process”, 10th International Conference on Kansei Engineering and Emotion Research 2022 (KEER2024), OAA-0035, pp.243-252, 2024-11 (Taichung, Taiwan).Best Conference Paper Award

[123]Keishi Ohya, Emmanuel Ayedoun, Masataka Tokumaru, “Evolutionary Music Synthesis: A Generative AI System with Interactive User Feedback”, Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on advanced Intelligent Systems (SCIS&ISIS 2024), M-2-G-2, 2024-11 (Himeji, Japan).

[122]Sora Yamamoto, Emmanuel Ayedoun, Masataka Tokumaru, “Exercise support system with self-growing avatars using interactive evolutionary computation”, Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on advanced Intelligent Systems (SCIS&ISIS 2024), M-1-E-1, 2024-11 (Himeji, Japan).

[121]Seiya Sakaguchi, Emmanuel Ayedoun, Masataka Tokumaru, “Virtual Agent Driven Peer Learning System to Enhance Exercise Motivation”, Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on advanced Intelligent Systems (SCIS&ISIS 2024), S-3-E-3, 2024-11 (Himeji, Japan).

[120]Ryoto Mikawa, Emmanuel Ayedoun, Masataka Tokumaru, “An IEC-driven Optimization of Gestures to Enhance Personality Traits in Communication Robots”, Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on advanced Intelligent Systems (SCIS&ISIS 2024), S-1-E-5, 2024-11 (Himeji, Japan).

[119]Yotaro Fuse, Emmanuel Ayedoun, Masataka Tokumaru, “Group Norm Awareness of Mobile Robots in Virtual Space Multi-Agent Simulation”, 26th International Conference on Human–Computer Interaction (HCII2024), LNCS 14685, pp. 91–104, 2024–07 (Washington DC, USA).

[118]Akira Inaba, Emmanuel Ayedoun, Masataka Tokumaru, “Toward Natural Human-Robot Interaction: A Dialogue Management Model for Modulating Social Dialogue Distance”, The 24th International Symposium on Advanced Intelligent Systems, TA6-2, pp.256-261, 2023-12 (Gwangju, Korea).

[117]Kaito Nagayasu, Emmanuel Ayedoun, Masataka Tokumaru, “Enhancing Movie Discovery: A Serendipity-Driven Recommendation System based on Temporal Relevance of Color Features”, The 24th International Symposium on Advanced Intelligent Systems, TM1-4, pp.18-24, 2023-12 (Gwangju, Korea).

[116]Yuri Kanazawa, Emmanuel Ayedoun, Masataka Tokumaru, “Impact of Robot Appearance and Attitude Changes on Human Impressions: a Preliminary Study”, The 24th International Symposium on Advanced Intelligent Systems, TM1-3, pp.12-17, 2023-12 (Gwangju, Korea).

[115]Yuya Tsubokura, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru, “Combining Kansei Retrieval and GAN to Foster Personalized Illustration Generation”, The 24th International Symposium on Advanced Intelligent Systems, TM1-2, pp.6-11, 2023-12 (Gwangju, Korea).

[114] *Hiroshi Takenouchi, Shion Isayama, Masataka Tokumaru, “Automatic Virtual Makeup System Using User–Preference Information”, HCI International 2023 Posters, Communications in Computer and Information Science, Vol 1836, Springer, pp.523-529, 2023-07 (Copenhagen, Denmark).

[113] Akihiro Yoshida, Emmanuel Ayedoun, Masataka Tokumaru, “Leveraging Cross-Modal Effects to Support Squat Exercise”, The 9th International Symposium on Affective Science and Engineering (ISASE 2023), PM-1B-04, 2023-02 (Online).

[112] Rikuto Kobayashi, Emmanuel Ayedoun, Masataka Tokumaru, “Rhythm Correction System for Promoting Motivation Toward Exercise”, Joint 12th International Conference on Soft Computing and Intelligent Systems and 23th International Symposium on advanced Intelligent Systems (SCIS&ISIS 2022), W-3-G-2, 2022-11 (Online and Onsite, Ise-Shima, Mie, Japan).

[111] Yotaro Fuse, Ryota Nomoto, Emmanuel Ayedoun, Masataka Tokumaru, “Impression of Robots Adaptively Refraining from Actions in Human–Robot Cooperative Scenario”, Joint 12th International Conference on Soft Computing and Intelligent Systems and 23th International Symposium on advanced Intelligent Systems (SCIS&ISIS 2022), T-3-H-2, 2022-11 (Online and Onsite, Ise-Shima, Mie, Japan).

[110] Fuma Yamamoto, Emmanuel Ayedoun, Masataka Tokumaru, “Human-Robot Interaction Environment to Enhance the Sense of Presence in Remote Sports Watching”, Joint 12th International Conference on Soft Computing and Intelligent Systems and 23th International Symposium on advanced Intelligent Systems (SCIS&ISIS 2022), T-3-H-1, 2022-11 (Online and Onsite, Ise-Shima, Mie, Japan).

[109] *Hiroshi Takenouchi, Masataka Tokumaru, “Applying Direct Manipulation of Prefered Clothes to Kansei Retrieval Agent System with Fuzzy Reasoning”, Joint 12th International Conference on Soft Computing and Intelligent Systems and 23th International Symposium on advanced Intelligent Systems (SCIS&ISIS 2022), F-2-F-1, 2022-11 (Online and Onsite, Ise-Shima, Mie, Japan).

[108] Tetsufumi Nakata, Emmanuel Ayedoun, Masataka Tokumaru, “Proposing a Collaborative Multi-agents System for English Learning Support”, 6th Workshop on Computer-Supported Personalized and Collaborative Learning, Proceedings of the 30th International Conference on Computers in Education, Vol. II, pp. 547-552, 2022-11 (Online and Onsite Kuala Lumpur, Malaysia).

[107] Yusuke Sakabe, Emmanuel Ayedoun, Masataka Tokumaru, “Leveraging IEC and others’ viewpoints presentation to foster breeding of creative IoT gadgets”, 10th Workshop on Technology-Enhanced STEM Education, Proceedings of the 30th International Conference on Computers in Education, Vol. II, pp. 311-317, 2022-11 (Online and Onsite Kuala Lumpur, Malaysia).

[106] Emmanuel Ayedoun, Satoko Inoue, Hiroshi Takenouchi, Masataka Tokumaru, “Combining IGA and KG for Serendipitous Learning Contents Recommendation”, Proceedings of the 4th Edition of Knowledge-aware and Conversational Recommender Systems Workshop (KaRS2022) @ACM RecSys2022, CEUR-WS, Vol.3294, No.2, pp. 12-17, 2022-09, (Online and Onsite Seattle, USA).

[105] *Hiroshi Takenouchi, Masataka Tokumaru, “Running Shoe Design System with Artificial Bee Colony Method using Gaze Information”, 9th International Conference on Kansei Engineering and Emotion Research 2022 (KEER2022), SES A3: Fashion&Textile, 2022-09 (Barcelona, Spain).

[104] Emmanuel Ayedoun, Masataka Tokumaru, “Towards Emotionally Expressive Virtual Agent to Foster Independent Speaking Tasks: a Preliminary Study”, In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2022 Posters. HCII 2022. Communications in Computer and Information Science, vol 1582. pp. 12-18, Springer, Cham. https://doi.org/10.1007/978-3-031-06391-6_2, 2022-6 (Online).

[103] Yotaro Fuse, Biina Ashida, Emmanuel Ayedoun, Masataka Tokumaru, “Decision-Making Model for Robots that Consider Group Norms and Interests”, In: Kurosu, M. (eds) Human-Computer Interaction. Technological Innovation. HCII 2022. Lecture Notes in Computer Science, vol 13303, pp. 475-485, Springer, Cham. https://doi.org/10.1007/978-3-031-05409-9_35, 2022-6 (Online).

[102] *Hiroshi Takenouchi, Airi Hattori, Masataka Tokumaru, “Music Recommendation System Considering Musical Score Features using Kansei Retrieval Agents with Fuzzy Inference”, Proceedings of ISASE2022, PM-2A-6, https://doi.org/10.5057/isase.2022-C000025, 2022-3 (Online).

[101] Emmanuel Ayedoun, Marina Goto, Masataka Tokumaru, “Towards Dynamic Formation of Online Discussion Groups: Capturing Variations in Group Members’ Interests based on Topics Flow”, Proceedings of ISASE2022, PM-1A-3, https://doi.org/10.5057/isase.2022-C000034, 2022-3 (Online).

[100] Takuto KAWAI, Masataka Tokumaru, Emmanuel Ayedoun, “Human Impressions on Imperfect Robots in Cooperative Relationship”, Proceedings of ISASE2022, PM-2A-4, https://doi.org/10.5057/isase.2022-C000028, 2022-3.

[99] Lingkai Wang, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru, “Optimization of fuzzy rules in sports highlight extraction method based on genetic algorithm”, Proceedings of ISASE2022, PM-2A-5, https://doi.org/10.5057/isase.2022-C000029, 2022-3 (Online).

[98] *Yuka Nishimura, Hiroshi Takenouchi, Masataka Tokumaru, “Reasoning Method in Character Coordination System Using Fuzzy Reasoning”, The 22nd International Symposium on Advanced Intelligent Systems (ISIS2021), G08-4.P00019, 2021-12 (Online and onsite at Cheongju, Korea).

[97] *Atsushi Ashida, Masataka Tokumaru, Tomoko Kojiri, “Narrative Discourse Structure Creation Support System for Reflecting Theme and Emotional Impression”, Proceedings of the 29th International Conference on Computers in Education, Vol.2, pp.697-699, 2021-11 (Online).

[96] *Hiroshi Takenouchi, Masataka Tokumaru, “Applying Artificial Bee Colony Algorithm to Interactive Evolutionary Computation”, The 7th International Conference on Biometrics and Kansei Engineering (ICBAKE2021) in International Conference on Computer Information Systems and Industrial Management (CISIM2021), pp.214-224, Springer, Cham, 2021-09 (Online and onsite at Ełk, Poland).

[95] Yotaro Fuse, Masataka Tokumaru, “Personal Space Norms Aware Robotic Navigation Model and Its Evaluation in a Virtual Reality Environment”, HCI International 2021 – Posters. HCII 2021. Communications in Computer and Information Science, vol 1420, pp.123-130, Springer, Cham, 2021-07 (Online).

[94] Ikuya Edama, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru: “Kansei Perception Support System to Promote Daily Life Awareness”, HCI International 2021 – Posters. HCII 2021. Communications in Computer and Information Science, vol 1420, pp.241-248, Springer, Cham, 2021-07 (Online).

[93] Shimpei Maruoka, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru: “User Preference and Suitability-Aware Eyeglasses Recommender System”, HCI International 2021 – Posters. HCII 2021. Communications in Computer and Information Science, vol 1419, pp.358-365, Springer, Cham, 2021-07 (Online).

[92] Satoko Inoue, Masataka Tokumaru, “Serendipity Recommender System for Academic Disciplines”, 2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS&ISIS 2020), #1570662369, pp.1-4, 2020-12 (Online).

[91] Yotaro Fuse and Masataka Tokumaru, “Investigation of a Human’s Opinion Affected by Social Influence of a Group Norm in a Human-Robot Group After a Human-Robot Scenario”, 2020 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings, SS-0362, 2020-12 (Canberra, Australia: Online).

[90] *Yuka Nishimura, Hiroshi Takenouchi, Masataka Tokumaru, “Preference Similarity Analysis of User Preference Rules Using a Character Coordination System”, HCI International 2020 – Posters Part 1, pp.167-172, 2020-07 Copenhagen, Denmark: Online).

[89] *Chawakorn Chaichanawirote, Masataka Tokumaru, Siam Charoenseang, “A Robot Agent that Learns Group Interaction Through a Team-Based Virtual Reality Game Using Affective Reward Reinforcement Learning”, HCI International 2020 – Posters Part 2, pp.163-168, 2020-07 (Copenhagen, Denmark: Online).

[88] Hiroaki Tanazawa, Masataka Tokumaru, “A survey of the effects of non-emotional motion features on emotion”, The 6th International Symposium on Affective Science and Engineering (ISASE2020), 4-A-5, 2020-03 (Tokyo, Japan).

[87] Chihiro Morita, Masataka Tokumaru, “Optimization Model to Express Emotions of Pet Robot”, The 6th International Symposium on Affective Science and Engineering (ISASE2020), 4-A-3, 2020-03 (Tokyo, Japan).

[86] Ryo Ito, Masataka Tokumaru, “A sticker-based dialog system considering shared emotions in group chat”, The 6th International Symposium on Affective Science and Engineering (ISASE2020), 4-A-2, 2020-03 (Tokyo, Japan).

[85] Yuya Kondo, Hiroshi Takenouchi, Masataka Tokumaru, “Recommender system based on personal Kansei evaluation tendency”, The 6th International Symposium on Affective Science and Engineering (ISASE2020), 4-A-1, 2020-03 (Tokyo, Japan).

[84] Yotaro Fuse, Hiroshi Takenouchi, Masataka Tokumaru, “Evaluation of Robotic Navigation Model Considering Group Norms of Personal Space in Human–Robot Communities”, The International Conference on Artificial Intelligence and Computational Intelligence, SAT2-B1, 2020-01 (Hanoi, Vietnam).

[83] Yotaro Fuse, Masataka Tokumaru, “An Investigation of Social Influence of Group Norms on Human in Human-Robot Groups”, 2019 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings, pp.1407-1414, 2019-12 (Xiamen, China).

[82] Narundo Kouno, Hiroshi Takenouchi, Masataka Tokumaru, “An Exercise Promotion System that Considers User Preferences”, the 20th International Symposium on Advanced Intelligent Systems (ISIS2019) & International Conference on Biometrics and Kansei Engineering (ICBAKE 2019), pp.427-434, 2019-12 (Jeju, Korea).

[81] Ryuta Katsuta, Masataka Tokumaru, “Role Recognition Model for Robots in a Group”, the 20th International Symposium on Advanced Intelligent Systems (ISIS2019) & International Conference on Biometrics and Kansei Engineering (ICBAKE 2019), pp.312-319, 2019-12 (Jeju, Korea).

[80] *Ryota Shiraishi, Yuka Nishimura, Hiroshi Takenouchi, Masataka Tokumaru, “Character Coordination System for Acquiring User Preference Rules”, the 20th International Symposium on Advanced Intelligent Systems (ISIS2019) & International Conference on Biometrics and Kansei Engineering (ICBAKE 2019), pp.261-268, 2019-12 (Jeju, Korea).

[79] *Hiroshi Takenouchi, Masataka Tokumaru, “Applying Hybrid Genetic Algorithm–Tabu Search Method to an Interactive Evolutionary Computation with Gaze Information”, the 20th International Symposium on Advanced Intelligent Systems (ISIS2019) & International Conference on Biometrics and Kansei Engineering (ICBAKE 2019), pp.253-260, 2019-12 (Jeju, Korea).

[78] Kosuke Furukawa, Hiroshi Takenouchi, Masataka Tokumaru, “Photo-arrangement Design System Considering Relations among Objects in the Real Environment”, the 20th International Symposium on Advanced Intelligent Systems (ISIS2019) & International Conference on Biometrics and Kansei Engineering (ICBAKE 2019), pp.239-246, 2019-12 (Jeju, Korea).

[77] Motoki Hayakawa, Masataka Tokumaru, “Model of a Robot for Forming Its Personality Based on Experience of Interaction in a Group”, the 20th International Symposium on Advanced Intelligent Systems (ISIS2019) & International Conference on Biometrics and Kansei Engineering (ICBAKE 2019), pp.172-179, 2019-12 (Jeju, Korea).

[76] Naoki Kaji, Hiroshi Takenouchi, Masataka Tokumaru, “T-Shirt Image Generation System Considering User Preference Using
Generative Adversarial Networks”, the 20th International Symposium on Advanced Intelligent Systems (ISIS2019) & International Conference on Biometrics and Kansei Engineering (ICBAKE 2019), pp.158-165, 2019-12 (Jeju, Korea).

[75] *Atsushi Ashida, Masataka Tokumaru, Tomoko Kojiri, “Novel Writing Support System by Target Readers’ Story Arcs and Characters’ Emotional Changes”, 27th International Conference on Computers in Education, Conference Proceedings Volume 1, pp.22-31, 2019-12 (Kenting, Taiwan).

[74] Ryota Shiraishi, Hiroshi Takenouchi, Masataka Tokumaru, “Optimization of Fuzzy Rules in Kansei Retrieval Agent with Fuzzy Reasoning”, 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems (SCIS&ISIS 2018), pp.449-454, 2018-12 (Toyama, Japan).

[73] *Minatsu Fujisaki, Hiroshi Takenouchi, Masataka Tokumaru, “Developing Female Clothing Coordination Generation System Using Eye Tracking Information”, Human-Computer Interaction. Interaction Technologies Volume 10903 of the series Information Systems and Applications, incl. Internet/Web, and HCI(the proceedings of HCI International 2018), pp.247-257, 2018-07 (Las Vegas, USA).

[72] *Hiroshi Takenouchi, Masataka Tokumaru, “Development of Interactive Evolutionary Computation Catalog Interface with User Gaze Information”, HCI International 2018 – Posters’ Extended Abstracts Volume 850 of the series Communications in Computer and Information Science, pp.121-128, 2018-07 (Las Vegas, USA).

[71] Yotaro Fuse, Hiroshi Takenouchi, Masataka Tokumaru, “A Convergence of Decision-making Criterions in a Human-robot Group – The Robot Makes a Suitable Decision-making Criterion by Interacting with the Group Members –”, The 4th International Symposium on Affective Science and Engineering and the 29th Modern Artificial Intelligence and Cognitive Science (ISASE-MAICS 2018), A1-1, 2018-05 (Spokane, WA, USA).

[70] *Hiroshi Takenouchi, Masataka Tokumaru, “Performance Evaluation of Interactive Evolutionary Computation Applying Gaze Information”, The 4th International Symposium on Affective Science and Engineering and the 29th Modern Artificial Intelligence and Cognitive Science (ISASE-MAICS 2018), A2-3, 2018-05 (Spokane, WA, USA).

[69] Hiroki Isoda, Hiroshi Takenouchi, Masataka Tokumaru, “Gaze-Voting Interface for Interactive Evolutionary Computation Considering the Kansei Evaluation of Multiple People”, 7th International Conference on Kansei Engineering and Emotion Research 2018, pp.29-38, 2018-03 (Kuching, Sarawak, Malaysia).

[68] Shigeru Ota, Hiroshi Takenouchi, Masataka Tokumaru, “Kansei clothing retrieval system using features extracted by autoencoder”, 2017 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings, pp.281-287, 2017-11 (Honolulu, Hawaii, USA).

[67] Yotaro Fuse, Hiroshi Takenouchi, Masataka Tokumaru, “A Robot Model in Limited Scenarios to Create a Suitable Decision-making Criterion by Interacting
with People in a Group”, 2017 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings, pp.104-110, 2017-11 (Honolulu, Hawaii, USA).

[66] Anna Tanaka, Hiroshi Takenouchi, Masataka Tokumaru, “Enhancing the Appropriateness of the Communicative Responses of Robots -a novel response-suppression model based on interaction with human interlocutors-“, The 18th International Symposium on Advanced Intelligent Systems : ISIS2017, pp.487-494, 2017-10 (Daegu, Korea).

[65] Yotaro Fuse, Hiroshi Takenouchi, Masataka Tokumaru, “A Model for Robot of Decision Making for Selecting Cooperative Behaviors in a Group”, The 18th International Symposium on Advanced Intelligent Systems : ISIS2017, pp.479-486, 2017-10 (Daegu, Korea).

[64] *Minatsu Fujisaki, Hiroshi Takenouchi, Masataka Tokumaru, “Interactive Evolutionary Computation Using Multiple Users’ Gaze Information”, HCI International 2017 – Posters’ Extended Abstracts Volume 713 of the series Communications in Computer and Information Science, pp.109-116, 2017-07 (Vancouver, Canada).

[63] *Hiroshi Takenouchi, Masataka Tokumaru, “Wrist Watch Design System with Interactive Evolutionary Computation”, HCI International 2017 – Posters’ Extended Abstracts Volume 714 of the series Communications in Computer and Information Science, pp.497-504, 2017-07 (Vancouver, Canada).

[62] Takanori Nakamura, Hiroshi Takenouchi, Masataka Tokumaru, “Emotional Action Generation Model Supporting Real-time Operation”, Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS 2017), Paper ID: #173, 2017-06 (Otsu, Japan).

[61] Yusuke Soga, Hiroshi Takenouchi, Masataka Tokumaru, “Interactive Evolutionary Computation Method using Disliked Individual Selection”, Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS 2017), Paper ID: #285, 2017-06 (Otsu, Japan).

[60] Xiang Yu, Hiroshi Takenouchi, Masataka Tokumaru, “Behavior Expression Model based on Structural Model of the Human Psyche for Robots with Growth Function”, International Symposium on Affective Science and Engineering 2017 (ISASE2017), B1-2, 2017-03 (Tokyo, Japan).

[59] Yuki Tsukada, Hiroshi Takenouchi, Masataka Tokumaru, “Sympathy Expression Model of Robots Considering Turn-Taking in Multiple Communication”, International Symposium on Affective Science and Engineering 2017 (ISASE2017), B1-3, 2017-03 (Tokyo, Japan).

[58] Masayoshi Inoue, Hiroshi Takenouchi, Masataka Tokumaru, “Music Recommendation System Improvement Using Distributed Genetic Algorithm”, 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems and 2016 17th International Symposium on Advanced Intelligent Systems (SCIS&ISIS 2016), pp.627-630, 2016-08 (Sapporo, Hokkaido, Japan).

[57] *Hiroshi Takenouchi, Masataka Tokumaru, “Performance Evaluation of a Kansei Retrieval Agent Model with Neural Networks”, 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems and 2016 17th International Symposium on Advanced Intelligent Systems (SCIS&ISIS 2016), pp.857-861, 2016-08 (Sapporo, Hokkaido, Japan).

[56] Masataka Tokumaru, Ayataka Yonezawa, “Nail art design system using interactive evolutionary computation with VR”, HCI International 2016 – Posters’ Extended Abstracts Volume 618 of the series Communications in Computer and Information Science, pp.552-557, 2016-07 (Toronto, Canada).

[55] A.Hoshino, H.Takenouchi, M.Tokuamaru, “Healthcare System that Suggests Personalized Exercises and Meals”, 16th International Symposium on Advanced Intelligent Systems (ISIS2015), F5c-1, pp.1460-1467, 2015-11 (Mokpo, Korea).

[54] Y.Hayashi, R.Oku, H.Takenouchi, M.Tokuamaru, “Consideration of Ingredient Purchases Using the Healthy Eating Habits Support System”, 16th International Symposium on Advanced Intelligent Systems (ISIS2015), F1e-1, pp.794-803, 2015-11 (Mokpo, Korea).

[53] *H.Takenouchi, M.Tokuamaru, “Membership Function Optimization of Kansei Retrieval Agents with Fuzzy Reasoning”, 16th International Symposium on Advanced Intelligent Systems (ISIS2015), F3a-5, pp.1152-1159, 2015-11 (Mokpo, Korea).

[52] M.Inoue, H.Takenouchi, M.Tokuamaru, “Music Recommendation System Using Kansei Agent and Music Fluctuation Properties”, 16th International Symposium on Advanced Intelligent Systems (ISIS2015), F1d-3, pp.760-768, 2015-11 (Mokpo, Korea).

[51] *H.Takenouchi, M.Tokumaru, “Applying a Hybrid IGA-SimE Algorithm to a Multimedia Retrieval System”, The 7th International Conference on Awareness Science & Technology (iCAST2015), Paper No.19, 2015-09 (Qinhuangdao, China).

[50] A.Fukumoto, H.Takenouchi, M.Tokumaru, “Verification of Differences in Growth due to Mutual Influence of Parent and Child Robots with Emotional Growth Functions”, The 1st International Symposium on Affective Science and Engineering (ISASE2015), D2-2, 2015-3 (Tokyo, Japan).

[49] K.Yamamoto, H.Takenouchi, M.Tokumaru, “Emoticon Selection Support System Using Emotional Learning”, The 1st International Symposium on Affective Science and Engineering (ISASE2015), C2-2, 2015-3 (Tokyo, Japan).

[48] *H.Takenouchi, H.Inoue, M.Tokumaru, “Signboard Design System with Votes by Many People”, 2014 IEEE Symposium Series on Computational Intelligence (SSCI 2014), ISIC2014 proceedings, pp.14-19, 2014-12 (Orlando, Florida, USA).

[47] M.Sakai, H.Takenouchi, M.Tokumaru, “Design Support System with Votes from Multiple People using Digital Signage”, 2014 IEEE Symposium Series on Computational Intelligence (SSCI 2014), ISIC2014 proceedings, pp.26-31, 2014-12 (Orlando, Florida, USA).

[46] R.Oku, H.Takenouchi, M.Tokumaru, “Effectiveness of Kansei model in Healthy Eating Habits Support System”, Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent Systems (SCIS & ISIS 2014), pp.335-338, 2014-12 (Kitakyusyu, Japan).

[45] S.Kinoshita, H.Takenouchi, M.Tokumaru,”An Emotion-Generation Model for a Robot that Reacts after Considering the Dialogist”, 7th IEEE International Conference Humanoid, Nanotechnology, Information Technology Communication and Control, Environment and Management (HNICEM2014), IS-09, 2014-11 (Puert Prinsesa, Palawan, Philippines).

[44] S.Iguchi, H.Takenouchi, M.Tokumaru,”Sympathy Expression Model for the Bystander Robot in Group Communication”, 7th IEEE International Conference Humanoid, Nanotechnology, Information Technology Communication and Control, Environment and Management (HNICEM2014), ROB-02, 2014-11 (Puert Prinsesa, Palawan, Philippines).

[43] S.Domae, H.Takenouchi, M.Tokumaru, “Virtual Dressing System for Fashion Coordination Using Parallel Retrieval Interactive Tabu Search”, HCI International 2014 – Posters’ Extended Abstracts Communications in Computer and Information Science Volume 434, pp.404-409, 2014-06 (Crete, Greece).

[42] M.Tokumaru, “Implementation of an Emotional Virtual Creature with a Growth Function Model”, HCI International 2014 – Posters’ Extended Abstracts Communications in Computer and Information Science Volume 434, pp.475-479, 2014-06 (Crete, Greece).

[41] M.Tokumaru, “Implementation of the Healthy Eating Habits Support System Based on User Taste Preferences and Nutritional Balance”, International Conference on Kansei Engineering and Emotion Research 2014, pp.1299-1312, 2014-06 (Linköping, Sweden).

[40] A.Fukumoto, H.Nagano, M.Tokumaru, “Care Action Generation Model for Robot as Parent Child Interaction with Emotion Growth Functions”, 14th International Symposium on Advanced Intelligent Systems – ISIS2013, T1c-4, 2013-11 (Daejeon, Korea).

[39] K.Yamamoto, M.Tokumaru, “Emoticon Recommendation System Using a Similarity Ratio of Emoticon Appearance”, 14th International Symposium on Advanced Intelligent Systems – ISIS2013, T3b-1, 2013-11 (Daejeon, Korea).

[38] S.Domae, H.Takenouchi, M.Tokumaru, “Parallel Retrieval Interactive Tabu Search”, 14th International Symposium on Advanced Intelligent Systems – ISIS2013, T3f-2, 2013-11 (Daejeon, Korea).

[37] H.Nagano, M.Harata, M.Tokumaru, “Developing sophisticated robot reactions by long-term human interaction”, the 15th International Conference on Human-Computer Interaction: Human-Computer Interaction, Towards Intelligent and Implicit Interaction, Lecture Notes in Computer Science Volume 8008, 2013, pp 319-328, 2013-07 (Las Vegas, Nevada, USA).

[36] Y.Inoue, T.Inoue, M.Tokumaru, “Collaborative Design Support System Based on Interactive Genetic Algorithm(IGA)”, the 15th International Conference on Human-Computer Interaction: HCI International 2013 – Posters’ Extended Abstracts, Communications in Computer and Information Science Volume 373, 2013, pp.685-689, 2013-07 (Las Vegas, Nevada, USA).

[35] Y.Inagawa, J.Hakamata, M.Tokumaru, “A Support System for Healthy Eating Habits: Optimization of Recipe Retrieval”, the 15th International Conference on Human-Computer Interaction, HCI International 2013 – Posters’ Extended Abstracts, Communications in Computer and Information Science Volume 374, 2013, pp.168-172, 2013-07 (Las Vegas, Nevada, USA).

[34] H.Nagano, M.Harata, M.Tokumaru, “A mutual effect model of desires and emotions in emotion for robots with growth function”, Joint 6th International Conference on Soft Computing and Intelligent Systems and 13th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2012), pp.197-202, 2012-11 (Kobe, Japan).

[33] T.Urai, D.Okunaka, M.Tokumaru, “Clothing image retrieval based on a similarity evaluation method for Kansei retrieval system”, Joint 6th International Conference on Soft Computing and Intelligent Systems and 13th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2012), pp.261-265, 2012-11 (Kobe, Japan).

[32] Y.Inagawa, J.Hakamata, M.Tokumaru, “A framework of recommender system considering the variety of Kansei”, Joint 6th International Conference on Soft Computing and Intelligent Systems and 13th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2012), pp.197-202, 2012-11 (Kobe, Japan).

[31] A.Ishikawa, Y.Tokumi, M.Tokumaru, “Recipe data coding method by using cooking process and quantity of nutrients for healthy eating habits support system”, Joint 6th International Conference on Soft Computing and Intelligent Systems and 13th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2012), pp.197-202, 2012-11 (Kobe, Japan).

[30] T.Yokoyama, H.Takenouchi, M.Tokumaru, N.Muranaka, “Website Design System Based on an Interactive Genetic Algorithm Using Tournament Evaluation by Multiple People”, Joint 6th International Conference on Soft Computing and Intelligent Systems and 13th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2012), pp.197-202, 2012-11 (Kobe, Japan).

[29] H.Takenouchi, M.Tokumaru, N.Muranaka, “Performance Evaluation of Interactive Evolutionary Computation with Tournament-Style Evaluation”, WCCI 2012 IEEE World Congress on Computational Intelligence, pp.193-200, 2012-06 (Brisbane, Australia).

[28] H.Takenouchi, T.Hirokata, M.Tokumaru, N.Muranaka, “Running Shoe Design System with Interactive Evolutionary Computation”, International Conference on Kansei Engineering and Emotion Research 2012, pp.925-932, 2012-05 (Penghu, Taiwan).

[27] M.Harata, H.Sumitomo, M.Tokumaru, “Emotion generation model for a robot with a growth function”, 12th International Symposium on Advanced Intelligent Systems – ISIS2011, pp.319-322, 2011-10 (Suwon, Korea).

[26] Y.Tokumi, J.Hakamata, M.Tokumaru, “Development of a healthy eating habits support system considering user’s taste and health: Generation of menus that are considered nutritionally balanced”, 12th International Symposium on Advanced Intelligent Systems – ISIS2011, pp.167-170, 2011-10 (Suwon, Korea).

[25] J.Hakamata, Y.Tokumi, M.Tokumaru, “Development of a healthy eating habits support system that presents menus considering a user’s taste and health: Optimization of Kansei retrieval system”, 12th International Symposium on Advanced Intelligent Systems – ISIS2011, pp.479-482, 2011-10 (Suwon, Korea).

[24] D.Okunaka, M.Tokumaru, “Kansei retrieval model using a Neural Network”, 12th International Symposium on Advanced Intelligent Systems – ISIS2011, pp.483-485, 2011-10 (Suwon, Korea).

[23] T.Inoue, M.Tokumaru, “Effectiveness of an Interactive Genetic Algorithm system based on the poker method”, 12th International Symposium on Advanced Intelligent Systems – ISIS2011, pp.171-173, 2011-10 (Suwon, Korea).

[22] T.Nakajima, Y.Kita, M.Tokumaru, “A move-action learning model using a recurrent neural network for a robot ~voluntary action by operant conditioning~”, 12th International Symposium on Advanced Intelligent Systems – ISIS2011,pp.489-491, 2011-10 (Suwon, Korea).

[21] T.Yamaguchi, N.Muranaka, M.Tokumaru, “Evaluation of Online Handwritten Characters for Penmanship Learning Support System”, 14th International Conference on Human – Computer Interaction (HCI International 2011) : Human-Computer Interaction, Part IV, HCII 2011, LNCS 6764, pp. 121–130, 2011-07 (Orlando, Florida, USA).

[20] T.Matsuo, H.Katayama, M.Tokumaru, N.Muranaka, “Sensitivity Information Analysis of Running Shoes Using Fuzzy Decision Tree and Visualization of Analytical Results”, Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2010), pp.156-160, 2010-12 (Okayama, Japan).

[19] H.Takenouchi, M.Tokumaru, N.Muranaka, “Interactive Genetic Algorithm with Tournament Evaluation Applying Win-Loss Result Presumption by Multiple People”, Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2010), pp.687-692, 2010-12 (Okayama, Japan).

[18] T.Hirokata, M.Tokumaru, N.Muranaka, “Interactive Tabu Search vs. Interactive Genetic Algorithm”, 9th International Conference on Entertainment Computing, Entertainment Computing – ICEC2010, pp.505-507, Springer, 2010-09 (COEX seoul, Korea).

[17] Y.Kita, M.Tokumaru, N.Muranaka, “Study on an Information Processing Model with Psychological Memory for a Kansei Robot”, 9th International Conference on Entertainment Computing, Entertainment Computing – ICEC2010, pp.490-492, Springer, 2010-09 (COEX seoul, Korea).

[16] H.Sumitomo, M.Tokumaru, N.Muranaka, “Study on an Emotion Generation Model for a Robot Using a Chaotic Neural Network”, 9th International Conference on Entertainment Computing, Entertainment Computing – ICEC2010, pp.502-504, Springer, 2010-09 (COEX seoul, Korea).

[15] T.Yamaguchi, M.Tokumaru, N.Muranaka, “Penmanship Learning Support System: Feature Extraction for Online Handwritten Characters”, 9th International Conference on Entertainment Computing, Entertainment Computing – ICEC2010, pp.496-498, Springer, 2010-09 (COEX seoul, Korea).

[14] M.Tokumaru, N.Muranaka, “Kansei Impression Analysis Using Fuzzy Decision Tree”, Proc. of International Conference on Kansei Engineering and Emotion Research 2010, pp.1333-1342, 2010-03 (Paris, France).

[13] K.Inoue, M.Tokumaru, N.Muranaka, “Considering the Characteristics of Living Creatures for Kansei Robot Action Generation Using a Neural Network”, Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems, pp.50-55, 2008-09 (Nagoya).

[12] H.Takenouchi, M.Tokumaru, N.Muranaka,”An interactive genetic algorithm with tournament evaluation of individuals by multiple people”, Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems, pp.1061-1066, 2008-09 (Nagoya).

[11] M.Tokumaru, N.Muranaka, “An Evolutionary Fuzzy Color Emotion Model for Coloring Support Systems”， 2008 IEEE International Conference on Fuzzy Systems (FUZZ 2008), pp.408-413, 2008-06 (Hong Kong, China).

[10] M.Tokumaru, N.Muranaka, “Product-Impression Analysis Using Fuzzy C4.5 Decision Tree”， International Conference on Software Knowledge Information Management and Applications 2006, pp.122-127, 2006-12 (Chang Mai, Thailand).

[9] Takaaki Ohtake, Masataka Tokumaru, Noriaki Muranaka, Shigeru Imanishi, “Automatic Music Composing System by Chaotic Neural Network – Melody Coding by Separation of Pitch and Length”, The 8th World Multi-Conference on Systemics, Cybernetics and Informatics, Vol.1 Information Systems, Technologies and Applications, pp.114-119, 2004.7(Florida, USA).

[8] Masataka Tokumaru, Noriaki Muranaka, Shigeru Imanishi, “Fuzzy Decision Tree Analysis to Investigate What Has an Influence on Ease-of-Use and Preference with Products”, The 8th World Multi-Conference on Systemics, Cybernetics and Informatics, Vol.1 Information Systems, Technologies and Applications, pp.433-438, 2004.7(Florida, USA).

[7] Masataka Tokumaru, Noriaki Muranaka, Shigeru Imanishi, “Virtual Stylist Project -Examination of Adapting Clothing Search System to User’s Subjectivity with Interactive Genetic Algorithms -“, 2003 Congress on Evolutionary Computation, pp.1036-1043, 2003.12.

[6] Masataka Tokumaru, Toshihiko Fujibayashi, Noriaki Muranaka, Shigeru Imanishi, “Virtual Stylist Project – Dress Up Support System Considering User’s Subjectivity -“, 2002 International Conference on Fuzzy Systems and Knowledge Discovery, pp.207-211, 2002.11.

[5] Masataka Tokumaru, Noriaki Muranaka, Shigeru Imanishi, “Color Design Support System Considering Color Harmony”, 2002 IEEE World Congress on Computational Intelligence, CD-ROM, 2002.5.

[4] Masataka Tokumaru, Noriaki Muranaka, Shigeru Imanishi, “Color Image Judgement System using Fuzzy Reasoning”, Proc. of the Fourth Asian Fuzzy Systems Symposium, pp.58-62, 2000-05 (Tsukuba, Japan).

[3] Takanori Ashida, Kouji Tuji, Masataka Tokumaru, Noriaki Muranaka, Shigeru Imanishi, “Image Contours Extraction by Ternary 2 Digit Output System using Laplacian‐Gaussian Filter”, The Second Korea‐Japan Joint Symposium on Multiple‐Valued Logic, KJ‐JS‐MVL01, pp.19‐22, 2001-08 (Miyazaki, Japan).

[2] Masataka Tokumaru, Noriaki Muranaka, Shigeru Imanishi, “Color Image Judgement System using Fuzzy Reasoning”, Proc. of the Fourth Asian Fuzzy Systems Symposium, pp.58-62, 2000.5.

[1] Masataka Tokumaru, Kazumi Yamashita, Noriaki Muranaka, Shigeru Imanishi, “Membership Functions in Automatic Harmonization System”, Proc. of 28th IEEE International Symposium on Multiple-Valued Logic, pp.350-355, 1998-05 (Fukuoka, Japan).

Kansei Robots

admin — Tue, 27 Aug 2024 07:33:49 +0000

HCI Lab Research Topic: 感性ロボット

Not Just Smart Robots—Lifelike Robots!

In recent years, robots have become more familiar in our daily lives. In particular, communication robots like Sony’s “AIBO” and SoftBank’s “Pepper” have attracted attention. These robots respond to human speech and interact with us through gestures, emotional expressions, and conversation, providing entertainment and engagement. However, it’s hard to say that such robots have truly become widespread in our everyday lives. Although they initially gained popularity due to their novelty, their appeal has gradually faded. Why have communication robots struggled to secure a lasting place in society?
One possible reason is that users quickly lose interest in them because their behaviors are too mechanical and simplistic. That’s why the development of robots that exhibit lifelike behavior—robots that understand and embody the sensitivities of humans and animals—is becoming increasingly important.

Various Communication Robots

Robots with Emotions

Our lab conducts research focused on the keyword "Emotions". Emotions are an essential part of human nature and play a critical role in communication between people. Therefore, for a robot to understand human sensitivity and build friendly relationships with people, it needs to have the function of "emotion."

The presence or absence of such lifelike emotional functions creates a significant distinction between humans and robots. In other words, by giving robots emotions, they can become more familiar and relatable to humans.

Can Robots Grow Too?

An “emotion generation model” is a system that determines what kind of emotions a robot should generate in response to various stimuli. Researchers around the world are studying emotion generation models for robots. However, most of this research focuses on how robots with complex and pre-defined sets of emotions can select the most appropriate one in a given situation.

In our lab, we focus on a new perspective: the “development” of living beings. By giving robots the ability to gradually develop emotions as humans do during growth, we aim to create a more lifelike emotion generation process.

Emotional Development in Robots

Robots with Needs

We are also conducting research focusing on innate biological factors and “needs,” such as sleepiness and hunger. In real living beings, strong emotions like “frustration” or “anger” can arise from desires such as hunger or the need to eat. Therefore, these elements are deeply connected to emotions as well.

An imperfect robot

Furthermore, research is being conducted to enhance the human-likeness of robots by deliberately incorporating imperfect behaviors, such as hesitation or indecision. Traditional robots tend to execute instructed actions or speech in a straightforward and mechanical manner, which makes it difficult to describe their behavior as human-like. As a result, users may perceive the robot as merely a machine, making it hard to develop a sense of familiarity or emotional attachment, thereby hindering long-term engagement. To address this, the aim is to intentionally design imperfect behaviors in robots so that humans are more likely to feel a sense of warmth and approachability toward them.

Related Work

Adaptive Psychological Distance in Japanese Spoken Human-Agent Dialogue: A Politeness-Based Management Model

In this study, we propose a computational model that enables more human-like dialogue by dynamically adjusting the perceived social distance in human-robot conversations, based on politeness theory. Traditional robots often employ a generic, static conversational style that cannot adapt to changes in the level of intimacy, which contributes to the impression of mechanical interaction. To address this, our model systematically manipulates "linguistic politeness markers" and "conversational strategies" in Japanese dialogue contexts to realize psychological distance between the robot and the human. This research offers insights into interaction design in contexts like Japanese communication, where social distance is linguistically formalized, thereby contributing to the field of HCI. Furthermore, it is expected to deepen our understanding of how conversational agents can achieve more natural and context-aware interactions that align with human social expectations.

Verification of immersive experience through watching with robot groups considering emotional contagion

In this study, we focus on nonverbal information in human-robot communication and propose a virtual sports viewing environment using a group of robots that induce a sense of presence by altering emotions through emotional contagion. Since the global outbreak of COVID-19 in 2020, various methods of watching sports have gained attention. However, traditional viewing methods fail to reproduce the communication that occurs on-site, resulting in a lack of presence. To address this, our system deploys a group of robots programmed to dynamically express emotions through an emotional contagion model. By incorporating this approach, we aim to enhance the user's sense of immersion and satisfaction by accommodating nuances in emotional transmission and individual preferences.

References

Kinoshita, S., Takenouchi, H., & Tokumaru, M. (2014). 対話者を考慮した反応を行うロボットの感情生成モデル [Emotion generation model for robots responding with consideration of dialogue partners]. Proceedings of the 30th Fuzzy Systems Symposium of the Japanese Society for Fuzzy Theory and Intelligent Informatics, TA1-4, 342–347.

Nagano, H., & Tokumaru, M. (2013). 発達機能を持つロボットにおける長期的なインタラクションによる感情分化の検証 [Verification of emotional differentiation through long-term interaction with robots possessing developmental functions]. Proceedings of the 29th Fuzzy Systems Symposium of the Japanese Society for Fuzzy Theory and Intelligent Informatics, MC3-1, 123–128.

Akira Inaba, Emmanuel Ayedoun, Masataka Tokumaru, “Adaptive Psychological Distance in Japanese Spoken Human-Agent Dialogue: A Politeness-Based Management Model”, The 15th International Workshop on Spoken Dialogue Systems Technology, 2025-05 (Bilbao, Spain) (to appear).

Yamamoto, F., Ayedoun, E., & Tokumaru, M. (2024). 感情伝播を考慮したロボット集団との観戦による臨場感演出の検証 [Verification of immersive experience through watching with robot groups considering emotional contagion]. Proceedings of the 34th Soft Science Workshop of the Japanese Society for Fuzzy Theory and Intelligent Informatics, 4–2.

Kansei Retrieval Systems

admin — Tue, 27 Aug 2024 07:28:57 +0000

HCI Lab Research Topic: 感性検索システム

User's preference-aware kansei search!

Today, if you want information, you can easily obtain it by searching keywords on the internet. However, the amount of information that appears is enormous, making it difficult to find the information you truly want. For example, when trying to buy fashion goods online, the number of search results is so large that checking each product one by one to find items matching your preferences is a very time-consuming task. Our laboratory is working on developing a kansei search system that accurately retrieves desired information by considering the user’s preferences to solve this problem.

Realization of a Kansei Search System

Even with kansei search, it is not possible to accurately retrieve the desired information by understanding the user's sensibility from the start. To perform kansei search, the computer needs to learn the user's sensibility. So, how does the computer understand a person’s sensibility? Let's consider an example of learning a user's clothing preferences.

Process of Learning User Preferences

First, both the user and the computer evaluate a piece of clothing. At this time, the computer bases its evaluation on factors believed to influence a person’s impression of the clothing, such as color, pattern, and shape. Then, the computer learns the user’s preferences by comparing the differences between its own evaluation and the user’s evaluation. By repeating these steps, the computer can understand the user’s sensibility and also identify the clothing factors that influence the user’s evaluations.

Because human sensibility is extremely complex, fully understanding it remains a challenge. In this research, we aim to develop better methods for learning human sensibility and to create a kansei search system that is more convenient and innovative than traditional keyword-based search systems.

Related Work

Combining Kansei Retrieval and GAN to Foster Personalized Illustration Generation

This research focuses on the practical application of generative AI, which has seen remarkable advances in recent years. Traditionally, creating illustrations from scratch is a highly labor-intensive task. Therefore, we propose an illustration generation system that combines a kansei search agent with generative AI. This system can learn the user’s preferences and generate high-quality illustrations. Furthermore, by utilizing ControlNet, an extension feature of the Stable Diffusion generative model used in our system, it enables illustration generation based on user-drawn line art images. The combination of these technologies is expected to allow controlled generation that matches the user’s preferences while producing high-quality illustrations in a short time.

Product Recommendation System That Promotes Selection Using Dominance Structuring Process

This research proposes a recommendation system designed to facilitate user decision-making. In recent years, the use of recommendation systems on online shopping sites has increased significantly. However, conventional recommendation systems often suggest similar products, which can complicate users’ decision-making and potentially reduce post-purchase satisfaction. Our system calculates the importance of product attributes based on user preferences and computes evaluation scores for products. The proposed system consists of two stages: a "preference acquisition stage," where user preferences are inferred from selection information, and a "final decision-making stage," where the ultimate product choice is made. In the final decision-making stage, texts structured using a dominance structuring process are presented to users to encourage product selection. Experimental results confirmed that the proposed system effectively promotes decision-making through the dominance structuring process. This research is expected to reduce users’ hesitation during purchase and enable smoother final decisions. Additionally, by allowing users to confidently select products that match their preferences, it is anticipated to enhance post-purchase satisfaction.

References

Takaki Urai, Masataka Tokuamaru, “User Kansei Clothing Image Retrieval System”, Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.18, No.6 pp. 1044-1052, 2014-11.

Yuya Tsubokura, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru, “Combining Kansei Retrieval and GAN to Foster Personalized Illustration Generation”, The 24th International Symposium on Advanced Intelligent Systems, TM1-2, pp.6-11, 2023-12 (Gwangju, Korea).

Tetsuaki Togo, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru, “Product Recommendation System That Promotes Selection Using Dominance Structuring Process”, 10th International Conference on Kansei Engineering and Emotion Research 2022 (KEER2024), OAA-0035, pp.243-252, 2024-11 (Taichung, Taiwan).

Health and Exercise Support System

admin — Mon, 26 Aug 2024 09:30:43 +0000

HCI Lab Research Topic: 健康管理システム

Support the user's health!

In modern society, lifestyle-related diseases are viewed as a serious concern. In particular, solving the problem of obesity—which is considered a major cause of various lifestyle-related diseases—has been attracting attention. With the spread of accessible home exercise devices like Nintendo's Wii Fit, people have found it relatively easy to manage their health. Additionally, applications that utilize smartphone sensors can record data such as calories burned and changes in the user's weight. Furthermore, the use of wearable devices worn on the wrist or other parts of the body has enabled more precise measurement and recording of user information. However, existing applications do not offer personalized suggestions for diet or exercise tailored to an individual's lifestyle.
This research focuses on diet and exercise as components of health management, and aims to develop a health management system that provides personalized recommendations based on the user's individual needs.

Overview of the Health and Exercise Support System

The figure below illustrates an overview of the health management system. Based on the user's physical information, the system provides exercise and dietary recommendations tailored to their goals. In doing so, it is designed to suggest meals and exercises that align with the user's preferences in order to maintain their motivation for health management.

System Overview

A System for Recommending Exercises to Users

We introduce a system that presents exercises which fulfill the appropriate amount of physical activity for each user. The goal of this system is to generate exercise menus that combine various types of exercises to match the user's target intensity level. However, if users are repeatedly presented with similar exercise menus every day, their motivation to continue exercising may decrease. Therefore, in this study, we explored a system that offers a wide variety of exercise menus by utilizing approximately 200 types of exercises commonly used in fitness clubs.

Exercise Menus with Rich Variety

The effectiveness of the above system was confirmed through computer-based simulations. Moving forward, we aim to develop a more comprehensive system that not only provides exercise recommendations but also offers dietary suggestions and enables enjoyable health management through the use of wearable devices.

Related Work

Harmony Generation System to Enhance Motivation for Group Exercise

This study proposes a harmony generation system designed to enhance motivation for group exercise. The system generates sounds based on the movements of multiple users and enables collaborative musical performance by layering these individual sounds. Additionally, it supports the creation of harmonious output by correcting timing discrepancies in sound generation between users. In the experiment, participants performed various exercise patterns while the presence and degree of sound generation and correction were varied to evaluate the system's effectiveness.The results confirmed that musical collaboration through physical movement can increase the enjoyment of exercise in a group setting. Furthermore, adjusting the timing of each user's sound generation helped create a sense of unity, reduced psychological burden, and suggested an increase in users' motivation to exercise.

Leveraging Cross-Modal Effects to Support Squat Exercise

This study proposes a virtual reality (VR) system that utilizes the cross-modal effect—an interaction between visual and auditory senses—to create the illusion of reduced training load. The system employs a height-adjustable chair to help prevent users from losing balance during squat exercises and a non-see-through head-mounted display that projects a 3D scene responsive to the user's movements. An evaluation experiment was conducted to explore the relationship between immersion tendency and perceived fatigue. The results indicated that the system's support reduced subjective fatigue while having minimal impact on heart rate. Moreover, a noticeable discrepancy between the avatar's movements and those of the participants suggested that a stronger immersion tendency may contribute to an increase in perceived fatigue. These findings suggest that VR can be effectively used to reduce the subjective feeling of fatigue during exercise, potentially offering a more comfortable and engaging training experience.

References

Y.Hayashi, R.Oku, H.Takenouchi, M.Tokuamaru, ” Consideration of Ingredient Purchases Using the Healthy Eating Habits Support System”, 16th International Symposium on Advanced Intelligent Systems (ISIS2015), F1e-1, pp.794-803, 2015-11 (Mokpo, Korea).

Oku, R., Takenouchi, H., & Tokumaru, M. (2016, March). 食生活支援システムにおけるユーザの細やかな嗜好を表現する感性モデルの提案 [Proposal of an affective model representing users’ fine-grained preferences in dietary support systems]. Proceedings of the 11th Spring Conference of the Japan Society of Kansei Engineering, G3‑3, 2016, Kobe, Japan.

Hoshino, A., Takenouchi, H., & Tokumaru, M. (2017, March). ユーザの嗜好を考慮した運動を推薦する健康管理システム [Health management system recommending exercises that consider user preferences]. Proceedings of the 27th Soft‑Science Workshop of the Japanese Society for Fuzzy Theory and Intelligent Informatics, A4‑2, pp. 57–58, Akita, Japan.

Akihiro Yoshida, Emmanuel Ayedoun, Masataka Tokumaru, “Leveraging Cross-Modal Effects to Support Squat Exercise”, The 9th International Symposium on Affective Science and Engineering (ISASE 2023), PM-1B-04, 2023-03 (Online).

Kobayashi, R., Ayedoun, E., & Tokumaru, M. (2023, September). 集団運動の意欲向上を促すハーモニー生成システム [Harmony generation system to enhance motivation for group exercise]. Proceedings of the 39th Fuzzy Systems Symposium of the Japanese Society for Fuzzy Theory and Intelligent Informatics, 1F2‑1, pp.266–270, Nagano–Karuizawa, Japan.

Interactive Evolutionary Computation

admin — Sat, 24 Aug 2024 09:32:10 +0000

HCI Lab Research Topic: 感性検索システム

Let’s Create Something That Matches Your Sensibility with Interactive Evolutionary Computation!

Interactive Evolutionary Computation (IEC) is a method in which humans and computers collaborate to create something that aligns with human sensibilities. Examples of such creations include clothing design and color coordination, shoe design, fashion coordination, and even music and camera work in 3D spaces expressed as video—spanning a wide range of applications.

Overview of Interactive Evolutionary Computation

Now, let’s take a brief look at how IEC works.
For example, imagine a user wants to design running shoes they would like to wear while jogging.

First, the computer presents several running shoe design proposals to the user.

Next, the user evaluates the proposed designs based on their own sensibilities and preferences, with reactions such as “I like this design!” or “This one isn’t quite right…”

Then, the user’s feedback is sent back to the computer, which generates new design proposals based on the evaluations and presents them again to the user.

By repeating these steps, the system gradually generates designs that match the user’s sensibilities.

Overview of IEC

In recent years, product development fields have increasingly sought to create items that align with user sensibilities, and the application of IEC is gaining attention. However, a major challenge in IEC is the high evaluation burden placed on users. To reduce this burden, various approaches have been explored, including improvements to algorithms and evaluation interfaces. Our research focuses on reducing user evaluation burden through enhancements to the evaluation interface.

Improvement Policy for the Evaluation Interface

In conventional IEC, the typical evaluation interface requires users to assign a rating—such as on a 5-point or 10-point scale—to about 10 to 20 presented designs. However, this can cause users to hesitate in assigning scores, leading to a significant evaluation burden.

Evaluation Interface with a 10-Point Rating Scale

We therefore proposed an evaluation interface that avoids the cumbersome task of assigning numerical ratings. Instead, users simply select only the designs they prefer from the ones presented. To date, we have introduced several such interfaces, including the “Tournament-Based Evaluation Method,” where users evaluate designs in a bracket-style format, and “Interactive Tabu Search,” where users select only one preferred design from multiple options. In addition, we are also working on developing evaluation interfaces based on eye gaze and conversational input.

Evaluation via Tournament Format

In the tournament-based evaluation method, the user repeatedly compares two presented designs and selects the one they prefer. This approach is especially effective in reducing the evaluation burden when assessing time-based data such as music or video, as only two items are compared at a time.
There are two types of tournament-based evaluation methods: the "Standard Tournament Format," where the user selects their preferred design from the two presented, and the "Graded Tournament Format," where the user evaluates the two designs with nuanced preferences such as “strongly prefer the left design” or “slightly prefer the right design.”

Standard Tournament Format

Graded Tournament Format

Select Only One Preferred Design

In Interactive Tabu Search, the user selects only one preferred design from a set of presented options. While it is less suitable for evaluating time-based media such as music or video—due to the need to compare multiple items at once—it simplifies the evaluation process for static images, effectively reducing the user’s evaluation burden.

Interactive Tabu Search

Evaluation Experiments

Up to now, we have conducted both numerical simulations—using evaluation agents generated on a computer in place of real users—and user-based evaluation experiments. The numerical simulations were used to assess the fundamental performance of the proposed methods, while the user experiments focused on evaluating ease of use from the users’ perspective.
These results indicate that both the Tournament-Based Evaluation Method and Interactive Tabu Search are effective in reducing the evaluation burden on users in IEC.

We are also engaged in developing applied systems based on the Tournament-Based Evaluation Method and Interactive Tabu Search. Additionally, we are working on the development of a fundamental algorithm for Parallel Search Interactive Tabu Search, which allows users to select multiple preferred and non-preferred designs simultaneously.

Enhancing Movie Discovery: A Serendipity-Driven Recommendation System based on Temporal Relevance of Color Features

This study proposes a novel recommendation system for subscription-based movie streaming services, which have become increasingly popular in recent years. These platforms host vast libraries of movie content, often making it difficult for users to choose what to watch. To address this issue, many streaming services have implemented recommendation systems. However, traditional movie recommendation systems tend to rely on objective categorizations or subjective user ratings, which can lead to overly predictable suggestions.In contrast, our proposed system leverages temporal color data from films to introduce serendipity—the experience of unexpected yet pleasant discoveries—into the movie selection process. The goal is to provide recommendations that go beyond user expectations and introduce them to films they might not have otherwise encountered.Experimental results suggest the effectiveness of the proposed approach, showing that the system is capable of recommending unexpectedly enjoyable movies. This research opens up the possibility for users to discover new films they wouldn’t have come across through conventional recommendation systems, ultimately enhancing user satisfaction with the movie-watching experience.

An IEC-driven Optimization of Gestures to Enhance Personality Traits in Communication Robots

This study proposes a system that optimizes the gestures used by communication robots to express personality traits based on individual user preferences. For a communication robot to evoke a sense of familiarity and connection, it must convey a friendly impression. However, conventional robot personalities are typically designed based on generalized human impressions and do not account for the preferences of individual users.To address this issue, the proposed system employs Interactive Evolutionary Computation (IEC) to optimize the gestures that express a robot's personality in accordance with the specific preferences of the user. Experimental evaluations were conducted to verify the system’s effectiveness. The results suggest that the proposed approach can improve users’ impressions of the robot and enhance their sense of closeness to it.This research contributes to enabling robots to provide more natural and personalized communication, ultimately improving user satisfaction and fostering a greater sense of affinity toward the robot.

References

Hiroshi Takenouchi, Masataka Tokumaru, Noriaki Muranaka, “Tournament-style Evaluation using Kansei Evaluation”, International Journal of Affective Engineering, Vol.12, No.3, pp.395-407, 2013-09.

Takenouchi, H., Dommae, S., & Tokumaru, M. (2014). Construction of a virtual fitting system for men’s fashion coordination using parallel interactive tabu search [並列対話型タブーサーチを用いたメンズファッションコーディネートのための仮想試着システムの構築]. Proceedings of the 2014 IEICE General Conference, D‑8‑7. Niigata, Japan.

Takenouchi, H., Dommae, S., & Tokumaru, M. (2013). A Study on Parallel Search Interactive Tabu Search [並列探索を用いた対話型タブーサーチに関する検討]. Proceedings of the 27th Annual Conference of the Japanese Society for Artificial Intelligence, 203‑3in. Toyama, Japan.

Kaito Nagayasu, Emmanuel Ayedoun, Masataka Tokumaru, “Enhancing Movie Discovery: A Serendipity-Driven Recommendation System based on Temporal Relevance of Color Features”, The 24th International Symposium on Advanced Intelligent Systems, TM1-4, pp.18-24, 2023-12 (Gwangju, Korea).

Ryoto Mikawa, Emmanuel Ayedoun, Masataka Tokumaru, “An IEC-driven Optimization of Gestures to Enhance Personality Traits in Communication Robots”, Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on advanced Intelligent Systems (SCIS&ISIS 2024), S-1-E-5, 2024-11 (Himeji, Japan).