Abstract
In conversation, a speaker sometimes asks questions that relate to another speaker’s detailed personality, such as his/her favorite foods and sports. This behavior also appears in conversations with conversational agents; therefore, agents should be developed that can respond to such questions. In previous agents, this was achieved by creating question-answer pairs defined by hand. However, when a small number of persons create the pairs, we cannot know what types of questions are frequently asked. This makes it difficult to know whether the created questions cover frequently asked questions; therefore, such essential question-answer pairs for conversational agents are possibly overlooked. This study analyzes a large number of question-answer pairs for six personae created by many question-generators, with one answer-generator for each persona. The proposed approach allows many questioners to create questions for various personae, enabling us to investigate the types of questions that are frequently asked. A comparison with questions appearing in conversations between humans shows that 50.2% of the questions were contained in our question-answer pairs and the coverage rate was almost saturated with the 20 recruited question-generators.
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Sugiyama, H., Meguro, T., Higashinaka, R., Minami, Y. (2014). Large-scale Collection and Analysis of Personal Question-Answer Pairs for Conversational Agents. In: Bickmore, T., Marsella, S., Sidner, C. (eds) Intelligent Virtual Agents. IVA 2014. Lecture Notes in Computer Science(), vol 8637. Springer, Cham. https://doi.org/10.1007/978-3-319-09767-1_53
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DOI: https://doi.org/10.1007/978-3-319-09767-1_53
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