Translating Emotions to Annotations -- A Participant Perspective of Physiological Emotion Data Collection
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866917969226891264 |
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| author | Singh, Pragya Budhiraja, Ritvik Jalote, Pankaj Kumar, Mohan Singh, Pushpendra |
| author_facet | Singh, Pragya Budhiraja, Ritvik Jalote, Pankaj Kumar, Mohan Singh, Pushpendra |
| contents | Physiological signals hold immense potential for ubiquitous emotion monitoring, presenting numerous applications in emotion recognition. However, harnessing this potential is hindered by significant challenges, particularly in the collection of annotations that align with physiological changes since the process hinges heavily on human participants. In this work, we set out to study human participant perspectives in the emotion data collection procedure. We conducted a lab-based emotion data collection study with 37 participants using 360 degree virtual reality video stimulus followed by semi-structured interviews with the study participants. Our findings presented that intrinsic factors like participant perception, experiment design nuances, and experiment setup suitability impact their emotional response and annotation within lab settings. Drawing from our findings and prior research, we propose recommendations for incorporating participant context into annotations and emphasizing participant-centric experiment designs. Furthermore, we explore current emotion data collection practices followed by AI practitioners and offer insights for future contributions leveraging physiological emotion data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_19636 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Translating Emotions to Annotations -- A Participant Perspective of Physiological Emotion Data Collection Singh, Pragya Budhiraja, Ritvik Jalote, Pankaj Kumar, Mohan Singh, Pushpendra Human-Computer Interaction Physiological signals hold immense potential for ubiquitous emotion monitoring, presenting numerous applications in emotion recognition. However, harnessing this potential is hindered by significant challenges, particularly in the collection of annotations that align with physiological changes since the process hinges heavily on human participants. In this work, we set out to study human participant perspectives in the emotion data collection procedure. We conducted a lab-based emotion data collection study with 37 participants using 360 degree virtual reality video stimulus followed by semi-structured interviews with the study participants. Our findings presented that intrinsic factors like participant perception, experiment design nuances, and experiment setup suitability impact their emotional response and annotation within lab settings. Drawing from our findings and prior research, we propose recommendations for incorporating participant context into annotations and emphasizing participant-centric experiment designs. Furthermore, we explore current emotion data collection practices followed by AI practitioners and offer insights for future contributions leveraging physiological emotion data. |
| title | Translating Emotions to Annotations -- A Participant Perspective of Physiological Emotion Data Collection |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2503.19636 |