Voice interaction has entered daily life. Yet, the measurement of voice user experience (voice UX) remains underdeveloped. We took a consensus-based approach to the creation of a new instrument grounded in the work of voice UX researchers. For this, we conducted a systemic review of the literature from ACM, IEEE, and Web of Science ( ) to gather a corpus of instruments, measures, and methodological perspectives. We then carried out two validation studies on a range of computer voices, showing through exploratory ( ) and confirmatory factor analyses ( ) that five underlying factors unify the consensus-derived measures. We offer the 24-item Voice Experience Inventory (VOXI) alongside three comprehensive frameworks on key independent and dependent variables and their relationships, anchored to the material that guided our instrument development process. This work represents a timely and community-centred path towards rigorous and standardized measurement of voice UX.

Maldaimonic game experiences occur when people engage in personally fulfilling play through egocentric, destructive, and/or exploitative acts. Initial qualitative work verified this orientation and experiential construct for English-speaking Westerners. In this comparative mixed methods study, we explored whether and how maldaimonic game experiences and orientations play out in Japan, an Eastern gaming capital that may have cultural values incongruous with the Western philosophical basis underlying maldaimonia. We present findings anchored to the initial frameworks on maldaimonia in game experiences that show little divergence between the Japanese and US cohorts. We also extend the qualitative findings with quantitative measures on affect, player experience, and the related constructs of hedonia and eudaimonia. We confirm this novel construct for Japan and set the stage for scale development.

Dark patterns are deceptive and malicious properties of user interfaces that lead the end-user to do something different from intended or expected. While now a key topic in critical computing, most work has been conducted in Western contexts. Japan, with its booming app market, is a relatively uncharted context that offers culturally- and linguistically-sensitive differences in design standards, contexts of use, values, and language, all of which could influence the presence and expression of dark patterns. In this work, we analyzed 200 popular mobile apps in the Japanese market. We found that most apps had dark patterns, with an average of 3.9 per app. We also identified a new class of dark pattern: “Linguistic Dead-Ends” in the forms of “Untranslation” and “Alphabet Soup.” We outline the implications for design and research practice, especially for future cross-cultural research on dark patterns.

Japan faces many challenges related to its aging society, including increasing rates of cognitive decline in the population and a shortage of caregivers. Efforts have begun to explore solutions using artificial intelligence (AI), especially socially embodied intelligent agents and robots that can communicate with people. Yet, there has been little research on the compatibility of these agents with older adults in various everyday situations. To this end, we conducted a user study to evaluate a robot that functions as a facilitator for a group conversation protocol designed to prevent cognitive decline. We modified the robot to use backchannelling, a natural human way of speaking, to increase receptiveness of the robot and enjoyment of the group conversation experience. We conducted a cross-generational study with young adults and older adults. Qualitative analyses indicated that younger adults perceived the backchannelling version of the robot as kinder, more trustworthy, and more acceptable than the non-backchannelling robot. Finally, we found that the robot’s backchannelling elicited nonverbal backchanneling in older participants.