A Review of Affective Computing Research Based on Function-Component-Representation Framework
A Review of Affective Computing Research Based on Function-Component-Representation Framework
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DOI：
10.1109/taffc.2021.3104512
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发表时间：
2021-08
影响因子：
11.2
通讯作者：
Haiwei Ma;S. Yarosh
中科院分区：
文献类型：
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作者：
Haiwei Ma;S. Yarosh
情感计算是人类情感与计算技术之间差距的一个桥梁，近年来取得了显著的技术进步。然而，情感计算的理论基础很少讨论和评论。本文提供了一个彻底的概念分析的文献，了解情感计算和当前的答案必不可少的理论问题。受情感理论的启发，我们提出了功能-成分-表征（FCR）框架，将不同的情感概念组织成沿着三个维度，每个维度都解决了一个重要的问题：情感的功能（为什么计算情感），情感的成分（如何计算情感）和情感的表征（计算什么情感）。我们编码的影响，并发现对影响检测，行为成分和分类表示的偏好的基本概念，每一个文件。我们还观察到某些概念的耦合。例如，使用行为成分的论文倾向于采用分类表示，而使用生理成分的论文倾向于采用维度表示。FCR框架不仅是以系统和定量的方式组织不同理论观点的第一次尝试，也是帮助概念化AC项目并确定新可能性的蓝图。未来的工作可能会探讨如何确定频率的FCR框架组合可以在实践中应用。
Affective computing (AC), a field that bridges the gap between human affect and computational technology, has witnessed remarkable technical advancement. However, theoretical underpinnings of affective computing are rarely discussed and reviewed. This paper provides a thorough conceptual analysis of the literature to understand theoretical questions essential to affective computing and current answers. Inspired by emotion theories, we proposed the function-component-representation (FCR) framework to organize different conceptions of affect along three dimensions that each address an important question: function of affect (why compute affect), component of affect (how to compute affect), and representation of affect (what affect to compute). We coded each paper by its underlying conception of affect and found preferences towards affect detection, behavioral component, and categorical representation. We also observed coupling of certain conceptions. For example, papers using the behavioral component tend to adopt the categorical representation, whereas papers using the physiological component tend to adopt the dimensional representation. The FCR framework is not only the first attempt to organize different theoretical perspectives in a systematic and quantitative way, but also a blueprint to help conceptualize an AC project and pinpoint new possibilities. Future work may explore how the identified frequencies of FCR framework combinations may be applied in practice.