Motivations, emotions, and actions are inter-related essential factors in human activities. While motivations and emotions have long been considered at the core of exploring how people take actions in human activities, there has been relatively little research supporting analyzing the relationship between human mental states and actions. We present the first study that investigates the viability of modeling motivations, emotions, and actions in language-based human activities, named COMMA (Cognitive Framework of Human Activities). Guided by COMMA, we define three natural language processing tasks (emotion understanding, motivation understanding and conditioned action generation), and build a challenging dataset Hail through automatically extracting samples from Story Commonsense. Experimental results on NLP applications prove the effectiveness of modeling the relationship. Furthermore, our models inspired by COMMA can better reveal the essential relationship among motivations, emotions and actions than existing methods.
翻译:动机、情感和行动是人类活动中相互关联的基本要素。虽然长期以来人们一直把动机和情感视为探索人们如何在人类活动中采取行动的核心,但支持分析人类精神状态和行动之间关系的研究相对较少。我们提出了第一项研究,调查模拟人类基于语言的活动中的动机、情感和行动的可行性,名为COMMA(人类活动协调框架)。在COMMA的指导下,我们界定了三种自然语言处理任务(情感理解、动机理解和有条件的行动生成),并通过从Story Commonsense自动提取样本建立一个具有挑战性的数据集。关于NLP应用的实验结果证明了模拟关系的有效性。此外,我们受COMMA启发的模型可以比现有方法更好地揭示动机、情感和行动之间的基本关系。