This paper proposes a method with which an interview dialogue system can learn user-friendly dialogue strategies. Conventional interview dialogue systems mainly focus on collecting the user’s information and simply repeat questions. We have previously proposed a method for improving user impressions by engaging in small talk during interviews that performs frame-based dialogue management and generates small-talk utterances after the user answers the system’s questions. However, the utterance selection strategy in the method was fixed, making it difficult to give users a good impression of the system. This paper proposes a method for learning strategies for selecting system utterances based on a corpus of dialogues between human users and a text-based interview dialogue system in which each system utterance was evaluated by human annotators. This paper also reports the results of a user study that compared the proposed method with fixed utterance selection strategies.
CITATION STYLE
Nakamura, T., Kobori, T., & Nakano, M. (2019). Learning dialogue strategies for interview dialogue systems that can engage in small talk. In Lecture Notes in Electrical Engineering (Vol. 579, pp. 307–317). Springer. https://doi.org/10.1007/978-981-13-9443-0_27
Mendeley helps you to discover research relevant for your work.