Abstract
Knowledge workers are quite crucial to every enterprise, so exploring the relationship between their salary satisfaction and job performance is significant. Hence, this work observes their salary satisfaction by identifying the employees' emotions at the time of salary announcement. The relationship between salary satisfaction and job performance is studied through the obtained satisfaction. First, the convolutional neural network (CNN) model is introduced. Then, it is optimized by adding an attention mechanism to improve the accuracy of the emotion recognition model. Finally, through comparative experiments, the effectiveness of the model proposed and the impact of employee's salary satisfaction on job performance are verified. The experimental results show that the recognition accuracy of the model is much higher than that of the traditional model. In particular, the recognition accuracy of neutral emotions is as high as 95%. It verifies the effectiveness of the model.
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