出版社：The Japanese Society for Artificial Intelligence
摘要：Answer sentence generation is one of the important building blocks to achieve natural and smooth dialog in dialog systems. In conventional answer sentence generation, the system usually responds according to the user's topic or the information required by the user. However, having a dialog using only this information is not necessarily ideal. For example, in a persuasive dialog system that guides the user to the systems goal, only having a dialog according to the user's topic of interest may not achieve the systems goal. In this situation, it is important to be able to generate answers that guide users to topics related to the system goal. To achieve natural transitions from the current topic to the target topic, it is necessary to lead the conversation through related new topics that connect the current topic and the target topics. In this paper, we propose answer sentence generation methods for guiding users to new topics with answer templates. To effectively extract term pairs that apply to the handmade template from a term database, we take advantage of information from a concept dictionary and Web search. In addition, on the assumption that the user does not know the target topic, we prepare an explanation of each topic by hand. We build a dialog system that guides to the goal topic of the system from the input topic, as a method to evaluate if a dialog system using the proposed method can guide to the goal topic. We evaluate single answer sentences and the usage of the proposed method in a dialog system. The experimental results show the efficacy of the generated sentences.
关键词：dialog system ; guide topic ; relationships between terms ; answer sentence generation ; MDP
