徐振国， 张冠文， 孟祥增， 党同桐， 孔 玺
【关 键 词 】：
深度学习； 学习者情感； 情感识别； 智慧学习环境； 情感交互； 卷积神经网络
Learners' attention, memory, thinking and other cognitive activities can be affected by their own emotions. Accurate identification of learners' emotions is the basis of building harmonious emotional interaction in smart learning environment, and it is also an important means to judge learners' learning status. Traditional methods for learners' emotion recognition still have some problems such as low recognition rate, complex algorithm, poor robustness, and losing the key information of facial features easily. This paper proposes a learner emotion recognition method based on convolutional neural network, which consists of three convolutional layers, three pooling layers and one full connection layer. Then the training and experiments are carried out on the large-scale learner emotion database that is independently built. The experimental results show that this method can identify learners' emotions quickly and accurately. In the future, this method can be applied to the construction of smart learning environment to provide technical support for improving learner model, realizing emotional interaction and mining learning behavior.