基于知识拷贝机制的生成式对话模型

基于"编码—解码"结构的端到端生成式对话模型所生成的回复多样性差、信息量少,这在很大程度上阻碍了对话的进一步扩展和深入.而知识图谱作为一种高度结构化的知识,能够为对话提供相关知识以及话题转移关系,可以用来提升对话质量.因此,该文提出了一种基于知识拷贝机制的生成式对话模型,首先使用基于知识图谱的映射机制对对话内容进行处理...

Knowledge Copying Mechanism for Dialog Generation

The generative end-to-end dialog models suffer from generating monotonous and non-informative responses, which is a challenge in the dialog technology. As a highly structured knowledge source, knowledge graph can provide relevant information and topic transfer relationships that is essential to the continuation of the dialog. In this paper, a generative dialog model based on knowledge graph is proposed. First, a knowledge graph based mapping mechanism is used to process the dialog, then a copying mechanism is used to directly introduce the utterances contained in the knowledge graph into the generated responses and the information contained in knowledge graph is also used to guide the generation of responses by attention mechanism. On the "Knowledge-Driven Dialogue" dataset presented in the "2019 Language and Intelligent Competition", the proposed model outperforms the baseline model provided by competition organizer by 10.47% in character-level F₁ and 4.6% in DISTNCT-1, respectively.