Abstract：Dialog sentiment analysis aims to classify the sentiment of each sentence in a dialogue, considering both the speaker’s personal emotion and the emotion transmission between speakers. To model this with Transformer, this paper proposes a multi-party attention mechanism to better model the interaction between different speakers and simulate dialogue scenes. Experiments show that, compared with other SOTA models, Dialogue Transformer has simpler implementation, faster running speed, and an significantly increased Weighted-F1 value.
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