## 3 Question-Answer-Response Dialogue Model
### Utterance Selection in Each State
To compute the WER, we transcribed all participants utterances in the dialogue. The WER was used to confirm the difficulty of speech recognition in a dialogue with elderly people. #### 6.6.2 Dialogue Time

Dialogue time is the time from when the robot starts a dialogue until the robot ends the dialogue or a participant leaves the seat. Dialogue time was used to evaluate how long the twin-robot dialogue system can sustain a dialogue with elderly people. #### 6.6.3 Participant Utterance Time

Participant utterance time is the time that a participant spent speaking during a dialogue. By watching the video of the dialogue, we recorded the time when the participant started speaking and when he or she ended speaking. Participant utterance time was used to investigate whether participants participated positively during a dialogue. #### 6.6.4 Participant Subjective Impression

We asked a participant the following question: \"Did you feel something strange in that dialogue with the robot?\" The question was asked to elicit their viewpoint of the naturalness of the dialogue. Indeed, we needed to use formal psychological measures to obtain accurate results; however, this was quite challenging to accomplish for the elderly with dementia. #### 6.6.5 Caregiver Subjective Impression

We asked the caregivers the following question: \"Did the participant talk with the robot more positively, comparing to when he or she talked with staffs.\" The question used a 7-point Likert scale, in which one means'strongly disagree', and seven means'strongly agree'. The question was asked in order to find out if the participant had been in the same or different state as usual. ## 7 Results

We obtained the videos and the questionnaire results of 24 participants and analyzed the data. Although there had been 30 participants altogether, one participant could not continue a dialogue because he was not able to hear the robot's voice at all, while the other five participants had halted the dialogue owing to technical problems (e.g., network trouble, program bugs). The two-robot scenario had 13 participants, and one-robot scenario had 11 participants. We used the Mann-Whitney U test to compare data between the scenarios, and the alpha-level set at 0.05. We used a computer software 'jamovi' [59] for this test. ### Word Error Rate

Figure 7 shows the averages of the WERs. The total average of the WERs was 0.778 (SD = 0.144). The average of the WERs of the one-robot scenario was 0.789 (SD = 0.123), and that of the two-robot scenario was 0.768 (SD = 0.163). There was no significant difference between the scenarios (U = 62.0, \(p\) = 0.608, [PERSON]'s d = 0.148). ### Dialogue Time

Figure 8 shows the averages of the dialogue time. The total average of the dialogue time was 12 min 51 s (SD = 4 min 52 s). The average of the dialogue time of one-robot scenario was 11 min 30 s (SD = 5 min 18 s), and that of two-robot scenario was 14 min (SD = 4 min 20 s). Here, milliseconds were round off. There was no significant difference between the scenarios (U = 48.0, \(p\) = 0.188, [PERSON]'s d = \(-\)0.519). ### Participant Ulterance Time

Figure 9 shows the averages of the participant utterance time. The total average of the participant utterance time was 3 min 31 s (SD = 3 min 14 s). The average of the participant utterance time of one-robot scenario was 3 min 5 s (SD = 3 min 21 s), and that of two-robot scenario was 3 min 53 s (SD = 3 min 13 s). There was no significant difference between the scenarios (U = 61.0, \(p\) = 0.569, [PERSON]'s d = \(-\)0.242). Figure 8: Averages of the dialogue time in each scenario. Figure 7: The averages of the word error rate (WER) in each scenario. ### Participant Subjective Impression

Figure 10 shows the results of the question to the participants, which was whether the participants have felt something strange in a dialogue. The numbers of the participants who answered \"Yes\", \"No\", and nothing were 3 (13%), 17 (71%), and 4 (17%), respectively in total.