人工知能学会論文誌
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
特集論文「知的対話システム」
不特定多数のユーザが随時発話可能なライブストリーミングメディアにおけるアンドロイドロボットを用いた雑談対話システムの実現と評価
窪田 智徳小川 浩平石黒 浩
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2018 年 33 巻 1 号 p. DSH-G_1-13

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In this study, we developed and evaluated a dialogue system which enables an android robot to have a chat with users on Niconico Live provided by Dwango Co., Ltd. which is a live streaming service. In Niconico Live, broadcasters can talk to users who write comments displayed on the video stream. Therefore, by using Niconico Live chat, we eliminated speech recognition errors which can occur during speech conversations. In addition, the dialogue system can keep consistency of conversation by selecting the comment to which it can correctly respond because many comments are shown simultaneously on the video stream. The dialogue system was designed as a retrieval-based one which finds the appropriate response to user’s utterance from a dialogue corpus. Therefore, we collected a dialogue corpus containing 4,460 pairs of comments and robot responses by teleoperating the android robot talking with users, as a first step. In the next step, we completed the dialogue system on Niconico Live integrating the dialogue corpus into it. To evaluate the performance of the dialogue system, we recorded the conversation between the android and users while running the designed system. After that, we showed the recorded conversation to evaluators and asked them how they feel about the naturalness and consistency of the conversation. Results of the experiment indicate that Niconico Live users perceived the responses of the dialogue system to be natural and found the chat with the android entertaining. Through this study, we demonstrated the applicability of the dialogue system on Niconico Live. However, it is difficult to discuss its effectiveness when applying it to other situations or other communication media such as a humanoid robot or a virtual agent. Therefore, as a future work, conducting a comparative experiment might lead to better understanding of the effectiveness of the dialogue system for androids.

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© 人工知能学会 2018
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