Topic-enhanced emotional conversation generation with attention mechanism

作者：

Highlights：

• We present a topic-enhanced neural emotion conversation generation model (TE-ECG) with attention mechanism.

• The topic words are obtained from a pre-trained Twitter LDA model to ensure the generated response is related to the post.

• A novel dynamic emotional attention mechanism is proposed to capture the emotional context and topic information.

• The TE-ECG model can generate responses at both the emotion- and content-related levels.

摘要

•We present a topic-enhanced neural emotion conversation generation model (TE-ECG) with attention mechanism.•The topic words are obtained from a pre-trained Twitter LDA model to ensure the generated response is related to the post.•A novel dynamic emotional attention mechanism is proposed to capture the emotional context and topic information.•The TE-ECG model can generate responses at both the emotion- and content-related levels.

论文关键词：Emotional conversation,Topic model,Sequence-to-sequence,Attention mechanism

论文评审过程：Received 23 December 2017, Revised 3 September 2018, Accepted 6 September 2018, Available online 15 September 2018, Version of Record 21 November 2018.

论文官网地址：https://doi.org/10.1016/j.knosys.2018.09.006