Multi-stage Knowledge Dialogue System Based on Model Calibration and Control Code
Internet-based dialogue systems need to solve three problems:when to retrieve,what to retrieve and how to integrate dialogue history and external knowledge.In this paper,we split Internet-based dialogue systems into three stages,which are dialogue mode selection,query generation and response generation.Focusing on dialogue mode selection stage and response generation stage,we propose to use confidence calibration method to reduce false negative samples after mode classification.We also constrain model by control code to improve knowledge utilization for response generation.Finally,we propose two re-rankers to improve the dialogue generation performance.The experiments show that our method can exceed baseline models,and rank fourth in the knowledge grounded dialogue track of the 2022 Language and Intelligence Challenge.
knowledge-based dialogue systemnatural language processing
万方数据
维普
