A Study of Error Recovery Methods for User Information Acquisition in Daily Dialogue

Abstract

The purpose of this research is to develop a dialogue system that models its user’s preferences and experiences in daily dialogue. Understanding the user's preferences and experiences is important to increase the user's dialogue satisfaction. When acquiring user information, it is necessary to continue the dialogue according to the user's knowledge. In this paper, we propose a recovery method that tries to identify the intended concept in the user's utterance by comparing the user's utterance with the system's concept when it is not identified (error). The context of the dialogue is defined as a frame representation, and the system updates the context to identify the intended concept based on the information obtained from the user's previous utterances. In addition, when the user's utterance is ambiguous, it performs estimation to determine the intended concept. Here, it uses a common sense based on the experience data of third parties obtained in advance. The goal is to identify the intended concept without decreasing the user's motivation to talk. This kind of error recovery method is important not only for robust dialogue generation during user information acquisition, but also for promoting mutual understanding between users and the system.