Praiser
Praising behavior is one of important communication in daily life and social activities. Praising behavior is expected to build a good human relationship and improve human performance.However, some people are worried about how to behave in order to praise. In this study, we attempt to clarify the relationship between human behaviors and praising skills using actual dialogue data. Our approach to clarify the relationship between human behaviors and praising skills is as follows. Firstly, we construct a dialogue corpus include human behaviors and the evaluation values of praising skills. Secondly, we construct machine learning models to estimate praising skills from human behaviors. Finally, we analyze human behaviors for successfully praising a partner. This approach is expected to clarify the human behaviors that are important to successfully praising a partner. In addition, this approach is expected to improve praising skills and develop a system to give advice for successfully praising.
Journal articles
- Toshiki Onishi, Asahi Ogushi, Ryo Ishii, and Akihiro Miyata: Detecting Praising Behaviors Based on Multimodal Information. The IEICE Transactions on Information and Systems, Vol.xx, No.xx, pp.xx–xx (2025).
- Toshiki Onishi, Asahi Ogushi, Shunichi Kinoshita, Ryo Ishii, Atsushi Fukayama, and Akihiro Miyata: Detecting Praising Behavior Based on Multimodal Information in Remote Dialogue. Journal of Information Processing, Vol.33, pp.xx–xx (2025).
- Asahi Ogushi, Toshiki Onishi, Ryo Ishii, Atsushi Fukayama, and Akihiro Miyata: Predicting Praising Skills Using Multimodal Information in Remote Dialogue. Transactions of the Virtual Reality Society of Japan, Vol.29, No.3, pp.127–138 (2024).
- Toshiki Onishi, Arisa Yamauchi, Asahi Ogushi, Ryo Ishii, Atsushi Fukayama, Takao Nakamura, and Akihiro Miyata: Modeling Japanese Praising Behavior by Analyzing Audio and Visual Behaviors. Frontiers in Computer Science (2022).
International conferences
- Toshiki Onishi, Asahi Ogushi, Ryo Ishii, Atsushi Fukayama, and Akihiro Miyata. Prediction of Praising Skills Based on Multimodal Information. Proc. 12th International Conference on Affective Computing and Intelligent Interaction (ACII ’24), pp.xx–xx (2024).
- Asahi Ogushi, Toshiki Onishi, Yohei Tahara, Ryo Ishii, Atsushi Fukayama, Takao Nakamura, and Akihiro Miyata: Analysis of Praising Skills Focusing on Utterance Contents. Proc. 23rd Annual Conference of the International Speech Communication Association (Interspeech ’22), pp.2743–2747 (2022).
- Toshiki Onishi, Asahi Ogushi, Yohei Tahara, Ryo Ishii, Atsushi Fukayama, Takao Nakamura, and Akihiro Miyata: A Comparison of Praising Skills in Face-to-Face and Remote Dialogues. Proc. 13th Language Resources and Evaluation Conference (LREC ’22), pp.5805–5812 (2022).
- Toshiki Onishi, Arisa Yamauchi, Ryo Ishii, Yushi Aono, and Akihiro Miyata: Analyzing Nonverbal Behaviors along with Praising. Proc. 22nd ACM International Conference on Multimodal Interaction (ICMI ’20), pp.609–613 (2020).
This project is being conducted with NTT Corp.