Context-aware Conversational Management System for Human-robot Interaction by Incorporating User Query-based Context Classification

Context awareness in conversational human robot interaction is an interesting but still challenging topic in the research arena. Context awareness in conversational human robot interaction improves the human robot interaction by providing exact information to the user's queries as well as maintaining a human friendly interaction. We propose a conversational management system that is aware of the context of the user. Context awareness is identified from the verbal interactions with the user. In addition, a response cloud structure that is embedded in the conversational management system is presented to choose the appropriate responses for user queries, and at the same time, it can also be updated according to the wishes of the user. A user study was done to evaluate the performance of the system. The results of the user study show that the proposed method is suitable for domestic service robot-based applications.