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

Understand

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.