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This research involved 88 young adults aged between 20 years and 35 years from two different countries, Spain and Italy. This work aims to explore preferences of the two groups toward synthetic voices, created for the experiment with variations in gender and quality for each language. The Spanish group was asked to evaluate the two high-quality voices of Elena and Pablo and the two low-quality voices of Maria and Juan while the Italian group was asked to assess the high-quality voices of Giulia and Antonio and the low-quality voices of Clara and Edoardo. The shortened and digitized version of the Virtual Agent Voice Acceptance Questionnaire (VAVAQ) was administered, respectively, in the Spanish or Italian version on the basis of the referring group to collect participants’ preferences. Due to the pandemic situation, participants were mainly contacted via email. Each participant was provided with a specific link. Outcomes revealed that Spanish and Italian young adults showed a greater appreciation toward the high-quality female voice compared to the other proposed voices. Regarding participants’ cross-cultural differences, Italian participants seem to judge the voices as more emotionally engaging than the Spanish participants whereas Spanish participants consider the audited voices as more natural and expressive than the Italian participants.

As the influence of social robots in people’s daily lives grows, research on understanding people’s perception of robots including sociability, trust, acceptance, and preference becomes more pervasive. Research has considered visual, vocal, or tactile cues to express robots’ emotions, whereas little research has provided a holistic view in examining the interactions among different factors influencing emotion perception. We investigated multiple facets of user perception on robots during a conversational task by varying the robots’ voice types, appearances, and emotions. In our experiment, 20 participants interacted with two robots having four different voice types. While participants were reading fairy tales to the robot, the robot gave vocal feedback with seven emotions and the participants evaluated the robot’s profiles through post surveys. The results indicate that (1) the accuracy of emotion perception differed depending on presented emotions, (2) a regular human voice showed higher user preferences and naturalness, (3) but a characterized voice was more appropriate for expressing emotions with significantly higher accuracy in emotion perception, and (4) participants showed significantly higher emotion recognition accuracy with the animal robot than the humanoid robot. A follow-up study ($N=10$) with voice-only conditions confirmed that the importance of embodiment. The results from this study could provide the guidelines needed to design social robots that consider emotional aspects in conversations between robots and users.