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