DIEU: A Dynamic Interaction Emotion Unit for Emotion Recognition in Conversation

Emotion recognition in conversation (ERC) is challenging because the conversation takes place in real-time and the speakers interact with each other. However, existing methods ignore the dynamic characteristics of interaction between speakers, and the problem of long-range context propagation still exists. In this paper, we propose a Dynamic Interaction Emotion Unit (DIEU) to solve the above problems on the transcription of the conversation. First, we propose a main influence interval search algorithm to provide a dynamic interaction interval for each utterance. Then, we utilize the speaker-aware influence module and the two-stream context module to capture the dynamic interaction and the contextual information from this interval. Furthermore, to obtain the speaker state representation rich in emotional information we propose a novel dynamic routing algorithm to fuse the above information. These well-integrated state representations also enable our model to capture contextual information at a longer distance. Experiments on multiple datasets demonstrate the effectiveness of the proposed method.