تقرير
Hi-EF: Benchmarking Emotion Forecasting in Human-interaction
| العنوان: | Hi-EF: Benchmarking Emotion Forecasting in Human-interaction |
|---|---|
| المؤلفون: | Wang, Haoran, Mai, Xinji, Tao, Zeng, Wang, Yan, Yu, Jiawen, Zhou, Ziheng, Tong, Xuan, Yan, Shaoqi, Zhao, Qing, Gao, Shuyong, Zhang, Wenqiang |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning |
| الوصف: | Affective Forecasting, a research direction in psychology that predicts individuals future emotions, is often constrained by numerous external factors like social influence and temporal distance. To address this, we transform Affective Forecasting into a Deep Learning problem by designing an Emotion Forecasting paradigm based on two-party interactions. We propose a novel Emotion Forecasting (EF) task grounded in the theory that an individuals emotions are easily influenced by the emotions or other information conveyed during interactions with another person. To tackle this task, we have developed a specialized dataset, Human-interaction-based Emotion Forecasting (Hi-EF), which contains 3069 two-party Multilayered-Contextual Interaction Samples (MCIS) with abundant affective-relevant labels and three modalities. Hi-EF not only demonstrates the feasibility of the EF task but also highlights its potential. Additionally, we propose a methodology that establishes a foundational and referential baseline model for the EF task and extensive experiments are provided. The dataset and code is available at https://github.com/Anonymize-Author/Hi-EF. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.16406 |
| رقم الأكسشن: | edsarx.2407.16406 |
| قاعدة البيانات: | arXiv |
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