In order to effectively predict the speaker’s informing emotion from text fragments, we propose a transfer learning framework based on the BERT pre-training model through deep semantic feature extraction and cascade structure of dynamic weight linear classifier. In the speaker informing emotion prediction task, a 0.70 F1 score is achieved, illustrating the effectiveness of cross-domain emotion recognition.