**1. Introduction**

For elderly people, it is important to have opportunities to talk with someone daily. The act of talking with someone is a fundamental action for building social connectedness and reducing the feeling of social isolation. Social disconnectedness and perceived social isolation are likely to cause health risks [1–3], such as dementia [4,5], depression [6], and early death [7]. Therefore, it is important to increase opportunities for elderly people to have dialogues with other people.

However, increasing such opportunities are not as easy as they may seem. To see why, we considered a case in Japan, which is one of the countries with the highest rate of people aged 65 or over. Ninety percent of the elderly people who live with their families have dialogues every day in some ways including telephone calls and e-mails. However, only 54.3% of those who live alone do

so [8]. To increase opportunities for those living alone to have a dialogue, it was desirable for their family members, friends, neighbors, and hired caregivers to support them. Nonetheless, it was not easy for them to continue spending much time with the elderly people. In other words, there are limitations in human resources to support elderly people.

Social robots, including computer agents, are expected to increase opportunities for the elderly to engage in dialogues. Various applications of social robots for elderly people, such as schedule management, cognitive games, physical exercise suggestions, and information-provision [9,10], have been proposed so far. Although these applications can be useful in maintaining the health of elderly users, the aim of the applications is not to sustain a dialogue. Studies of communication for elderly people, for example Erber [11], Caris-Verhallen et al. [12], and Grainger [13], are premised on the idea that dialogue is important for elderly people. Furthermore, based on this idea, interventions that attempt to motivate residents of nursing care homes to interact with each other have been proposed; for example, staff training to raise awareness and to encourage caregivers to stimulate residents to interact [14–16]. Like these studies, under the assumption that much of the beneficial features of human social interaction is carried by dialogue, it does make sense to investigate whether these beneficial features of dialogue can also be realized by a non-human social agent. The first step towards producing and investigating such an application is to develop a system that can sustain a dialogue with elderly people for some time.

However, it is quite hard for robots to sustain a dialogue with the elderly. Kopp et al. [17] pointed out that "elderly users often have selectively impaired abilities, e.g., for auditory perception, articulation, adapting to a recommended interaction style, adhering to a clean turn-taking structure, or comprehending content of high information density [18,19]". In particular, the difficulty of speech recognition in a dialogue with elderly people [18] is a critical issue in sustaining a coherent dialogue. In commonly used chat-bot systems, speech recognition failures basically because of nonsense responses and results in dialogue breakdown. It is unclear how a robot could sustain a coherent dialogue for a while under the situation where speech recognition would frequently fail.

Our goal is to develop a robot dialogue system that can sustain a coherent dialogue with elderly people for some time and also provide good user experience with the dialogues. To achieve this goal, we propose a question–answer–response dialogue model in which a robot takes the initiative in the dialogue by asking a user, various questions. Moreover, we propose an approach to extend the model such that two robots can participate in the dialogue. To evaluate how these features influence user's dialogue time and user's dialogue experience, we implement a dialogue system with two robots called the twin-robot dialogue system and conduct a field trial using the twin-robot dialogue system in a nursing home. We report the details of the trial and the results and finally, we discuss the implication of the results.
