Distributed Representations of Emotion Categories in Emotion Space | |
Xiangyu, Wang2,3; Chengqing, Zong1,2,3 | |
2021 | |
会议日期 | August 1–6, 2021 |
会议地点 | online |
英文摘要 | Emotion category is usually divided into different ones by human beings, but it is indeed difficult to clearly distinguish and define the boundaries between different emotion categories. The existing studies working on emotion detection usually focus on how to improve the performance of model prediction, in which emotions are represented with one-hot vectors. However, emotion relations are ignored in onehot representations. In this article, we first propose a general framework to learn the distributed representations for emotion categories in emotion space from a given emotion classification dataset. Furthermore, based on the soft labels predicted by the pre-trained neural network model, we derive a simple and effective algorithm. Experiments have validated that the proposed representations in emotion space can express emotion relations much better than word vectors in semantic space. |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/52060] |
专题 | 模式识别国家重点实验室_自然语言处理 |
作者单位 | 1.CAS Center for Excellence in Brain Science and Intelligence Technology 2.School of Artificial Intelligence, University of Chinese Academy of Sciences 3.National Laboratory of Pattern Recognition, Institute of Automation, CAS |
推荐引用方式 GB/T 7714 | Xiangyu, Wang,Chengqing, Zong. Distributed Representations of Emotion Categories in Emotion Space[C]. 见:. online. August 1–6, 2021. |
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