A Syntactically Constrained Bidirectional-Asynchronous Approach for Emotional Conversation Generation
Hefei University of Technology（合肥工业大学）
英文摘要：
Traditional neural language models tend to generate generic replies with poor logic and no emotion. In this paper, a syntactically constrained bidirectional-asynchronous approach for emotional conversation generation (E-SCBA) is proposed to address this issue. In our model, pre-generated emotion keywords and topic keywords are asynchronously introduced into the process of decoding. It is much different from most existing methods which generate replies from the first word to the last. Through experiments, the results indicate that our approach not only improves the diversity of replies, but gains a boost on both logic and emotion compared with baselines.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
