## 2 Related Work
However, with regards to achieving a conversation for a long while, it appeared to have low conversation support. For robots specialized in assisting physical or cognitive activities, Ifbot could provide some activity programs such as Japanese language quizzes, singing songs, mouth exercise, and arithmetic. Although they used speech recognition in the programs, they said; \"Almost all participants may have been dissatisfied with the robot's speaking and voice recognition functions.\" [38]. Matilda is a human-like (in appearance and attributes; e.g., voice, expressions, gestures, emotions) assistive communication robot (service and companion) in nursing homes in Australia [39]. Although users' impression of Matilda was assessed through a field trial in the nursing homes (Australia), the dialogue between elderly participants and the robot was not mentioned. [PERSON] et al. [40] developed a dialogue robot system that chats with elderly people watching TV. This robot could provide responses by extracting social media comments related to TV programs. In addition to this function, the robot improves users' dialogue experience such as backchannel and repetition. However, the study did not evaluate the system with elderly people, and it did not consider dialogue breakdown due to speech recognition failures. [PERSON] et al. [41] developed a robot system that supported the co-imagination method for elderly people. With this robot system, elderly people talk to each other with a specified theme while looking at photos taken in their early lives. This method is designed to train the cognitive functions, which especially decline with aging, at an early stage of dementia [42]. The robot acts as a moderator of the conversation. Because the robot was remote-controlled by an operator, it is unclear how successful robot moderation between elderly participants is under the situation of frequent speech recognition failures. [PERSON] et al. [43] proposed a system that dynamically generated dialogue scenarios for counseling patients with dementia. In the study, personalized conversations were generated using the history obtained in conversation and linked open data. However, they did not care about the situation of speech recognition failures and the system had not yet been evaluated. [PERSON] proposed constructive dialogue models [44] and an architecture based on the model [45] for socially intelligent robots. A robot with this architecture can be aware of potentially interesting topics and of the user's attention, interest, and understanding through multimodal signals. Dialogue content is managed by topic tracking and anticipating possible continuations, calculated by coherence measures using the semantic distance between possible topics. With this architecture, [PERSON] et al. [45] developed an application, using a robot assistant that instructed the human user on various task procedures related to elder care support services. However, the architecture is not applied to engage in dialogues with the elderly and is not concerned with speech recognition failures. Through the above review, past studies of social assistive robots for elderly people appear to have paid little attention to speech recognition failure. They have not evaluated for how long dialogues with elderly participants had been continued. In contrast to the past studies, this paper focuses on developing and evaluating a robot dialogue system that can sustain a dialogue even in a situation where speech recognition frequently fails.