## 4 Experiment
### Effect of Response Delay and Emotional Expression  
Next, we analyzed the evaluation of each conversation shown in Table 7 to determine whether their evaluation values were affected by the response delay and emotional expression. Table 10 shows the result of the Multivariate Analysis of Variance (MANOVA) that investigates the effect of the emotional expression and the response delay upon all the evaluation values. As a result, we found a significant interaction between emotional expression and response delay (\(p=0.050\)), but the independent factor did not show significance. Table 11 shows the results of the Analysis of Variance (ANOVA) to evaluate differences among different response delay times and the presence of emotional facial expressions. In this analysis, the presence of emotional expression was treated as a categorical variable, and the response delay was regarded as a continuous variable. From these results, we found statistically significant differences in information accuracy (emotional expression), responsiveness (response delay), and satisfaction (emotional expression). We also found statistically significant differences in the interaction between the response delay and emotion for responsiveness. Figures 7-9 show the evaluation results of information accuracy, responsiveness, and overall satisfaction, respectively. As shown in Figures 7 and 9, the participants' perception of information accuracy and overall satisfaction increased when the agent changed facial expressions according to the emotion estimation; however, the response delay did not affect these evaluation results. The result of information accuracy seems to be related to the relationship between the speaker's facial expressions and trustworthiness, where showing a happy face increases the speaker's trustworthiness [52]. The overall satisfaction was not affected by the response delay, either. [PERSON] et al. reported that the satisfaction of dialogue systems monotonically decreased when the response delay increased [53]. Their dialogue system used only speech and did not have facial images; this difference could cause the different responses of the users to the response delay. \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Variable** & **Df** & **Pillai’s Trace** & **Approx. F** & **Df1** & **Df2** & \(p\) \\ \hline Response delay & 3 & 0.23772 & 0.7315 & 30 & 255 & 0.84712 \\ Emotion & 1 & 0.16986 & 1.6983 & 10 & 83 & 0.09470 \\ Delay \(\times\) Emotion & 3 & 0.45136 & 1.5053 & 30 & 255 & 0.04964 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Results of MANOVA. The independent variables are emotions and different response delays; the response variables are the 10 items shown in Table 7.  
Figure 6: The questionnaire result after each conversation. On the other hand, the evaluation values of responsiveness decreased along with increasing response delay when the agent did not change facial expressions. This is a natural response of the participants because the responsiveness includes the speed of the agent's answering behavior. Interestingly, the responsiveness value did not change for different response delays when the agent changed facial expressions according to emotion. Figure 8: Evaluation results of “responsiveness” with and without the agent’s emotional expression. The error bars indicate the standard error. The effect of response delay was statistically significant (\(p=0.026\)), but that of emotional expression was not (\(p=0.069\)). The interaction between the two factors was significant (\(p=0.038\)).