Hi-EF: Benchmarking Emotion Forecasting in Human-interaction
Fuente:
arXiv
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| Autori principali: | , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
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| _version_ | 1866917114665762816 |
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| author | Wang, Haoran Mai, Xinji Tao, Zeng Lin, Junxiong Tong, Xuan Pan, Ivy Yan, Shaoqi Wang, Yan Gao, Shuyong |
| author_facet | Wang, Haoran Mai, Xinji Tao, Zeng Lin, Junxiong Tong, Xuan Pan, Ivy Yan, Shaoqi Wang, Yan Gao, Shuyong |
| contents | Affective Forecasting is an psychology task that involves predicting an individual's future emotional responses, often hampered by reliance on external factors leading to inaccuracies, and typically remains at a qualitative analysis stage. To address these challenges, we narrows the scope of Affective Forecasting by introducing the concept of Human-interaction-based Emotion Forecasting (EF). This task is set within the context of a two-party interaction, positing that an individual's emotions are significantly influenced by their interaction partner's emotional expressions and informational cues. This dynamic provides a structured perspective for exploring the patterns of emotional change, thereby enhancing the feasibility of emotion forecasting. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_16406 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Hi-EF: Benchmarking Emotion Forecasting in Human-interaction Wang, Haoran Mai, Xinji Tao, Zeng Lin, Junxiong Tong, Xuan Pan, Ivy Yan, Shaoqi Wang, Yan Gao, Shuyong Computer Vision and Pattern Recognition Machine Learning Affective Forecasting is an psychology task that involves predicting an individual's future emotional responses, often hampered by reliance on external factors leading to inaccuracies, and typically remains at a qualitative analysis stage. To address these challenges, we narrows the scope of Affective Forecasting by introducing the concept of Human-interaction-based Emotion Forecasting (EF). This task is set within the context of a two-party interaction, positing that an individual's emotions are significantly influenced by their interaction partner's emotional expressions and informational cues. This dynamic provides a structured perspective for exploring the patterns of emotional change, thereby enhancing the feasibility of emotion forecasting. |
| title | Hi-EF: Benchmarking Emotion Forecasting in Human-interaction |
| topic | Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2407.16406 |