| dc.description.abstract | We hope that through reading in English, students will be interested in English, so that students can connect English with their own life through reading, and develop their language ability in the social context. However, such a social and cultural construction process requires a large number of teachers, which is not feasible under the current limited human resources.
Therefore, our dialogue system takes the story as the main axis to establish a common topic and start a dialogue with users. Our team hopes that the interaction between students and chatbots is not only a simple discussion of stories, but also a question-and-answer session in daily conversations or allowing students to appropriately However, this is still a challenge, because under the integration of multi-faceted modules, robots need to have sufficient natural language understanding and dialogue strategy selection capabilities, which can automatically and efficiently provide products that meet the needs of the current situation. situational response.
The main task of this article is to introduce how we train an educational dialogue robot model, so that it can detect the situation of students from various states, and then explore the corresponding replies of this combination of states. In this model, we use Reinforcement learning training architecture to achieve the ultimate goal of this paper - to establish a relationship with the user and make the dialogue perpetual. | en_US |