# Evaluation of Emotional Satisfaction Using Questionnaires in Voice-Based Human-AI Interaction
## 4 Discussion
### User Emotion Classification According to Design Parameters  
In this study, various styles of conversation based on four design parameters were presented in dialog with the VIS, and the emotions felt toward the users were evaluated. As a result of identifying the difference in emotion according to the level of the used design parameters, a difference in emotional satisfaction was observed depending on the number of trials and the sentence structure, and the response time and pace of the answer did not significantly affect the user's \"pleasurability\" and \"reliability.\" It can be seen that the number of trials and the sentence structure are more sensitive to changes in the user's emotions than the response time and pace of the answer. The response time and pace of the answer did not significantly affect emotion in this study, but since they are important parameters that can be changed in real products, it is judged that additional research needs to be conducted by diversifying the level of the parameters in order to confirm the change in emotion. In contrast, it was confirmed that the two design parameters (number of trials and sentence structure) that showed a statistically significant difference in emotional satisfaction were classified into three levels of pleasurability and four levels of reliability. Table 5 shows the structure of the level of satisfaction classification in an integrated manner for pleasurability and reliability.  
Table 5 shows that the user's emotions can be subdivided according to the style of conversation, rather than simply classifying satisfaction as high/low. As a result of this study, the form of dialogue that belongs to the highest level of satisfaction in the four levels of satisfaction classification was found to be one trial, when the question or the reference was mentioned. However, in terms of pleasurability, the number of trials was 1 and the reference was mentioned; in the case of reliability, the number of trials was 1, and the satisfaction was highest in the form of mentioning the question. This shows that there is a need to lead a conversation in a form tailored to a group that values reliability more among users and a group that values pleasurability more. To overcome this, the VIS must understand the characteristics of the user and secure a conversation that considers the user, and finally, establish a customized interaction. In this study, the possibility of classifying design parameters was secured, but an experiment was performed  
on 20 subjects that did not consider their characteristics. Therefore, among the variety of styles of conversations classified into four levels of satisfaction, there is a limitation in that it was not possible to identify the most suitable conversation type for individual users. Personalization and customization need to be fully implemented in order to optimize user-adaptive interactions, but there are still technical limitations. To overcome these limitations, it is necessary to secure as many user characteristics (human factors) as possible, and design accordingly. [PERSON] et al. described a novel music recommendation technique based on the identification of personality traits, moods, and emotions [36], and a novel recommender system that provides recommendations based on the interaction between users and multimedia content [37]. [PERSON] et al. [6] conducted a study to derive the human factors of a user that need to be considered when designing information systems for autonomous vehicles. If the user's human factors are structured, the VIS can be designed, and personalized interaction according to the human factors is possible; it is then possible to obtain a considerable level of personalization and customization. The limitations of this study can be supplemented by conducting subsequent evaluation studies.