Retrieval-Polished Response Generation for Chatbot

Retrieval-Polished Response Generation for Chatbot

Blog Article

Chatbot communication, in which a robot communicates with a human being in natural language in an open domain, has achieved significant progress.However, it still suffers from problems such as a lack of diversity and Tools contextual relevance.In this paper, we propose a retrieval-polished (RP) model for response generation that polishes a draft response based on a retrieved prototype.

In particular, we first adopt a prototype selector to retrieve a contextually similar prototype.Then, a generation-based polisher is designed to obtain a polished response.Finally, we introduce a polished response filter to Slate Cheese Board choose whether the final reply should be the retrieved response or the polished response.

Extensive experiments on a dialog corpus show that our method outperforms retrieval-based and generation-based chatbots with respect to fluency, contextual relevance, and response diversity.Specifically, our model achieves substantial improvement compared with several strong baselines.