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In this paper, we investigate the emotion recognition ability of thepre-training language model, namely BERT. By the nature of the framework ofBERT, a two-sentence structure, we adapt BERT to continues dialogue emotionprediction tasks, which rely heavily on the sentence-level context-awareunderstanding. The experiments show that by mapping the continues dialogue intoa causal utterance pair, which is constructed by the utterance and the replyutterance, models can better capture the emotions of the reply utterance. Thepresent method has achieved 0.815 and 0.885 micro F1 score in the testingdataset of Friends and EmotionPush, respectively.

EmotionX-IDEA: Emotion BERT -- an Affectional Model for Conversation