Abstract
In this paper, we proposed an emotion-aware video quality of experience (QoE) assessment. Specifically, we first detect the user's emotion via transfer learning. Then, we design a personalized video QoE prediction model. Experiments show that compared to the traditional video QoE assessment, emotion-aware video QoE assessment has higher score.
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