Evaluation of listening-oriented dialogue control rules based on the analysis of HMMs
Toyomi Meguro, Yasuhiro Minami, Ryuichiro Higashinaka, Kohji Dohsaka · 2011
We have been working on listening-oriented dialogues for the purpose of building listening agents. In our previous work [1], we trained hidden Markov models (HMMs) from listeningoriented dialogues (LoDs) between humans, and by analyzing them, discovered a distinguishing dialogue flow of LoD. For example, listeners suppress their information giving and selfdisclosure, and instead, increase acknowledgments and questions to elicit speakers ’ utterances. As an initial step for building listening agents, we decided to create dialogue control rules based on our analysis of the HMMs. We built our rule-based system and compared it with three other systems by a Wizard of Oz (WoZ) experiment. As a result, we found that our rule-based system achieved as much user satisfaction as human listeners. Index Terms: Listening-oriented dialogue, Dialogue system, Wizard of Oz