@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00241863,
 author = {Victor, Gaspard and Tipporn, Laohakangvalvit and Kaoru, Suzuki and Midori, Sugaya and Victor, Gaspard and Tipporn, Laohakangvalvit and Kaoru, Suzuki and Midori, Sugaya},
 book = {Proceedings of Asia Pacific Conference on Robot IoT System Development and Platform},
 month = {Dec},
 note = {In recent years, there has been a growing interest in real-time emotion-estimating robots, particularly for applications in nursing care and domestic settings. However, existing real-time emotion estimation robots often have limited speech possibilities based on the emotional states of the user. Addressing the increasing demand for enhanced human-robot interaction, this study focuses on refining the speech pattern of the emotion-estimating care robot. The goal is to uplift the emotional well-being of its users. A large set of sentences will then be tested on different participants, with the aim of implementing an algorithm that will learn from these experiments to determine the sentence pattern that will have the greatest impact on the user. The effectiveness of the approach is demonstrated by the final result, where the robot enunciates the sentences proven to have the most positive impact on the users, even causing them to laugh., In recent years, there has been a growing interest in real-time emotion-estimating robots, particularly for applications in nursing care and domestic settings. However, existing real-time emotion estimation robots often have limited speech possibilities based on the emotional states of the user. Addressing the increasing demand for enhanced human-robot interaction, this study focuses on refining the speech pattern of the emotion-estimating care robot. The goal is to uplift the emotional well-being of its users. A large set of sentences will then be tested on different participants, with the aim of implementing an algorithm that will learn from these experiments to determine the sentence pattern that will have the greatest impact on the user. The effectiveness of the approach is demonstrated by the final result, where the robot enunciates the sentences proven to have the most positive impact on the users, even causing them to laugh.},
 pages = {15--21},
 publisher = {情報処理学会},
 title = {Improving the Speech Pattern of an Emotion-aware Robot using EEG and HRV for Emotion Estimation},
 volume = {2024},
 year = {2024}
}