Emotion Estimation Method Based on Emoticon Image Features and Distributed Representations of Sentences
Emotion Estimation Method Based on Emoticon Image Features and Distributed Representations of Sentences
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DOI：
10.3390/app12031256
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发表时间：
2022-02-01
影响因子：
2.7
通讯作者：
Kita, Kenji
中科院分区：
文献类型：
--
作者：
Fujisawa, Akira;Matsumoto, Kazuyuki;Kita, Kenji
提出了一种基于表情符号图像特征和语言特征的表情识别方法。一些现有的方法在字典中注册表情符号和它们的面部表情类别并使用它们，而其他方法基于表情符号的各种元素来识别表情符号面部表情。然而，除非基于句子和表情符号的特征的组合，否则不能执行高精度的情感识别。因此，我们提出了一个模型，通过提取表情符号的形状特征，从他们的图像数据和应用的特征向量输入相结合的图像特征与特征提取的推文识别情绪。实验结果表明，该方法具有较高的识别准确率，比单纯使用文本特征的方法更有效。
This paper proposes an emotion recognition method for tweets containing emoticons using their emoticon image and language features. Some of the existing methods register emoticons and their facial expression categories in a dictionary and use them, while other methods recognize emoticon facial expressions based on the various elements of the emoticons. However, highly accurate emotion recognition cannot be performed unless the recognition is based on a combination of the features of sentences and emoticons. Therefore, we propose a model that recognizes emotions by extracting the shape features of emoticons from their image data and applying the feature vector input that combines the image features with features extracted from the text of the tweets. Based on evaluation experiments, the proposed method is confirmed to achieve high accuracy and shown to be more effective than methods that use text features only.