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Affective E-learning Platform Based on SVM

机译：基于支持向量机的情感在线学习平台

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摘要

The separation of teaching and learning in e-learning environments leads to the loss of emotion in the learning process which affects learners' interest, attention and efficiency, and causes difficulties in cooperation and communication with others. Therefore, technology of affective detection based on the physiological signals, which is in the e-learning platform of Southwest University in Chongqing, is applied to build learner's emotional model to solve this problem. Six emotions are detected, which are neutral (no affect), engagement, confusion, frustration, boredom and fatigue. Support Vector Machine is used to setup classification model. More engagement lead to better recognition accuracy. And a Research Agent is adopted to realize the computer's affective supports in e-learning based on the learner's emotional model. By using the technologies of affective detection and affective feedback, the system partly supports the affective communication between computer and human in e-learning.
机译：电子学习环境中的教与学分离导致学习过程中情感的流失，影响学习者的兴趣，注意力和效率，并给与他人的合作和沟通造成困难。因此，在重庆西南大学的电子学习平台中，基于生理信号的情感检测技术被应用来建立学习者的情感模型来解决这一问题。检测到六种情绪，这些情绪是中性的（无影响），订婚，混乱，沮丧，无聊和疲劳。支持向量机用于建立分类模型。参与度越高，识别精度越高。在学习者的情感模型的基础上，采用研究代理来实现计算机在电子学习中的情感支持。通过使用情感检测和情感反馈技术，该系统在电子学习中部分支持计算机与人之间的情感交流。

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