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A survey of emotion recognition methods with emphasis on E-Learning environments

机译:重点关注在线学习环境的情绪识别方法的调查

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Emotions play an important role in the learning process. Considering the learner's emotions is essential for electronic learning (e-learning) systems. Some researchers have proposed that system should induce and conduct the learner's emotions to the suitable state. But, at first, the learner's emotions have to be recognized by the system. There are different methods in the context of human emotions recognition. The emotions can be recognized by asking from the user, tracking implicit parameters, voice recognition, facial expression recognition, vital signals and gesture recognition. Moreover, hybrid methods have been also proposed which use two or more of these methods through fusing multi-modal emotional cues. In the e-learning systems, the system's user is the learner. For some reasons, which have been discussed in this study, some of the user emotions recognition methods are more suitable in the e-learning systems and some of them are inappropriate. In this work, different emotion theories are reviewed. Then, various emotions recognition methods have been represented and their advantages and disadvantages of them have been discussed for utilizing in the e-learning systems. According to the findings of this research, the multi-modal emotion recognition systems through information fusion as facial expressions, body gestures and user's messages provide better efficiency than the single-modal ones.
机译:情绪在学习过程中起着重要作用。考虑学习者的情绪对于电子学习(电子学习)系统至关重要。一些研究人员提出,系统应该诱导并引导学习者的情绪到合适的状态。但是,首先,学习者的情绪必须被系统识别。在人类情感识别中有不同的方法。可以通过向用户提问,跟踪隐式参数,语音识别,面部表情识别,生命信号和手势识别来识别情绪。此外,还提出了混合方法,其通过融合多模式情绪提示来使用这些方法中的两个或多个。在电子学习系统中,系统的用户是学习者。由于某些原因(已在本研究中进行了讨论),一些用户情感识别方法更适合于电子学习系统,而其中一些不合适。在这项工作中,对不同的情感理论进行了回顾。然后,介绍了各种情绪识别方法,并讨论了它们在电子学习系统中的优缺点。根据这项研究的结果,通过信息融合的多模式情感识别系统(如面部表情,身体手势和用户消息)比单模式具有更高的效率。

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