一个基于生理数据的真实世界数据集集群体情感经验
Patrícia Bota1,2, Joana Brito3, Ana Fred3,4
1Instituto de Telecomunicações, Avenida Rovisco Pais 1, Inst. Sup. Técnico, Torre Norte, Piso 10, 1049-001, Lisbon, Portugal. patricia.bota@tecnico.ulisboa.pt.
Scientific data
|January 23, 2024
概括
这项研究介绍了G-REx,这是一个新的数据集,用于使用生理信号识别真实世界的情绪. 它通过在自然主义的群组环境中收集数据,使得情感计算更准确.
科学领域:
- 情感计算是一种情感计算.
- 生理信号处理 物理信号处理
- 人与计算机的互动.
背景情况:
- 情感计算在面部情绪识别方面表现出色,但在整合生理数据方面扎.
- 现有的使用生理数据的情绪识别模型在实验室中表现良好,但在现实世界中表现不佳.
- 需要大规模的现实世界数据集来提高生理情绪识别的普遍性.
研究的目的:
- 介绍G-REx,这是一个新的数据集,旨在用于现实世界的情感计算.
- 通过在自然环境中收集的生理数据来开发强大的情绪识别系统.
- 促进在群体背景下对情绪识别的研究.
主要方法:
- 采集了用手腕戴式设备进行的光斑发热 (PPG) 和皮电活动 (EDA).
- 在群体环境中长时间观看电影时获取的数据.
- 在具有显著生理反应的段落上进行了回顾性情感注释.
主要成果:
- G-REx数据集包括来自190多名受试者的380多小时的数据,涉及31个以上的电影节.
- 数据收集侧重于现实世界的条件,模仿日常场景.
- 数据集的组设置为情感识别提供了上下文信息.
结论:
- G-REx为推进现实世界的情感计算提供了宝贵的资源.
- 数据集的设计促进了易于复制,鼓励进一步大规模收集数据.
- 这项工作解决了将生理情绪识别推广到日常生活中的差距.
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