Voice assistants (VAs) are typically evaluated through task performance metrics and self-report questionnaires, but people’s voices themselves carry rich paralinguistic cues that reveal affect, effort, and interaction breakdowns. We present a within-subjects study (N=49) that systematically compared three VA personas across three usage scenarios to investigate whether speech-derived audio features can serve as a proxy for user experience (UX). Participants’ speech was analyzed for temporal, spectral, and linguistic markers, alongside standardized UX measures, brief mood and stress ratings, and a post-study questionnaire. We found correlations between specific speech features and self-reported satisfaction and experience. Furthermore, a machine learning model trained on speech features achieved promising accuracy in classifying UX levels, indicating that this might be a reasonable alternative to self-report instruments. Our findings establish speech as a viable, real-time signal for implicitly measuring UX and point toward adaptive VUIs that respond dynamically to emotional and usability-related vocal cues.

This study investigates how avatar customization in virtual reality (VR) impacts trust formation between unacquainted individuals and how such trust transfers to subsequent face-to-face (FtF) meetings. A user study with 48 participants was conducted, where participants were assigned to either a “Similar-Self” condition, with avatars resembling their real-world appearance, or an “Alt-Self” condition, with creative avatars. The results showed that “Similar-Self” avatars led to higher initial integrity-based trust perceptions, though both avatar conditions exhibited similar trust growth during VR encounters. Trust carried over from VR to FtF with a brief recalibration period and ultimately increased beyond VR levels in FtF encounters. This research provides insights into how VR can support the development of trust in early-stage interactions and offers implications for Social VR platforms to better support trustworthy interactions across virtual-physical boundaries.

In virtual reality (VR), our virtual body can have different characteristics from our real body, such as appearance, size, and even extra body parts. Previous research shows that haptic feedback enhances the user-perceived embodiment of those dissimilar avatars. In particular, weight-shifting devices showed the potential to enhance arm deformation. However, there has been no exploration of using such techniques to enhance embodiment with extra body parts, like wings. We introduce HapticWings, a back-wearable 2D weight-shifting device that provides haptic feedback for wing motions, enhancing the user embodiment of avatars with extra wings. In three user studies, we explored (1) users’ abilities to recognize different weight-shifting motions provided by HapticWings, (2) users’ perceived embodiment of avatars with extra wings when providing haptic feedback for wing motions, and (3) four possible applications and used two of them to evaluate users’ sense of realism and enjoyment in VR.

Environmental haptic interfaces have been extensively researched for their ability to enhance spatial realism, diversity, and immersion in Virtual Reality (VR). Among these, the Overhead Haptic Interface (OHI) has shown unique interaction opportunities in VR, such as space design, training, and entertainment. However, direct touch interaction with encountered-type OHI and users' perceptual abilities in these contexts remain underexplored. In this paper, we introduce HaptiCeiling, an OHI utilizing a parallel mechanical system driven by three linear actuators. The system allows translational motion along the z-axis from 0 to$450 m m$and angular motion from −30 degrees to 30 degrees around both x and y-axes, enabling the rendering of various OHIs in VR. Through three user studies, we explored (1) just-noticeable difference (JND) in perceiving changes of HaptiCeiling's height and tilt angle, (2) the perceptual thresholds for virtual overhead interface height and tilt angle compared to HaptiCeiling without causing any semantic violations, and (3) the perceived realism and immersion of our system across three VR applications.

Thanks to the development of virtual reality (VR) technology, there is growing research on VR avatar body deformation effects. However, previous research mainly focused on passive body deformation expression, leaving users with limited methods to actively control their virtual bodies. To address this gap, we explored user-controlled forearm deformation by investigating how hand and forearm gestures can be mapped to various degrees of avatar forearm deformation. We conducted a gesture design workshop with six designers to generate gesture sets for different forearm deformations and deformation degrees, resulting in 15 gesture sets. Then, we selected the three highest-rated gesture sets and conducted a comparative study to evaluate the sense of embodiment and user performance across the three gesture sets. Our findings provide design suggestions for gesture-controlled forearm deformation in VR.

In the domain of Human-Computer Interaction, focus groups represent a widely utilised yet resource-intensive methodology, often demanding the expertise of skilled moderators and meticulous preparatory efforts. This study introduces the “Focus Agent,” a Large Language Model (LLM) powered framework that simulates both the focus group (for data collection) and acts as a moderator in a focus group setting with human participants. To assess the data quality derived from the Focus Agent, we ran five focus group sessions with a total of 23 human participants as well as deploying the Focus Agent to simulate these discussions with AI participants. Quantitative analysis indicates that Focus Agent can generate opinions similar to those of human participants. Furthermore, the research exposes some improvements associated with LLMs acting as moderators in focus group discussions that include human participants.

Locating out-of-view vehicles can help pedestrians to avoid critical traffic encounters. Some previous approaches focused solely on visualising out-of-view objects, neglecting their localisation and limitations. Other methods rely on continuous camera-based localisation, raising privacy concerns. Hence, we propose the ARcoustic system, which utilises a microphone array for nearby moving vehicle localisation and visualises nearby out-of-view vehicles to support pedestrians. First, we present the implementation of our sonic-based localisation and discuss the current technical limitations. Next, we present a user study (n = 18) in which we compared two state-of-the-art visualisation techniques (Radar3D, CompassbAR) to a baseline without any visualisation. Results show that both techniques present too much information, resulting in below-average user experience and longer response times. Therefore, we introduce a novel visualisation technique that aligns with the technical localisation limitations and meets pedestrians’ preferences for effective visualisation, as demonstrated in the second user study (n = 16). Lastly, we conduct a small field study (n = 8) testing our ARcoustic system under realistic conditions. Our work shows that out-of-view object visualisations must align with the underlying localisation technology and fit the concrete application scenario.

In this work, we describe our experience developing and evaluating the Cross-Reality Study Tool (CReST), which allows researchers to conduct and observe Virtual Reality (VR) user studies from an Augmented Reality perspective. So far, most research on conducting VR user studies has centred around tools for asynchronous setup, data collection and analysis, or (immersive) replays. Conversely, CReST is centred around supporting the researcher synchronously. We replicated three VR studies as example cases, applied CReST to them, and conducted an interview with one author of each case. We then performed a case study, and recruited 17 participants to take part in a user study where the researchers used CReST to observe participant interaction with virtual drawer and closet artefacts. We make CReST available for other researchers, as a tool to enable direct observation of participants in VR, and perform rapid, qualitative evaluations.

Previous works show that virtual reality itself can be used as a medium in which to stage an experimental evaluation. However, it is still unclear whether conventional usability evaluation methods can directly be applied to virtual reality evaluations and whether they will lead to similar insights when compared to equivalent real-world lab studies. Therefore, we conducted a user study with nine participants, comparing Heuristic Evaluation (HE) for the evaluations of a novel smart artefact. We asked participants to evaluate the physical prototype and their virtual counterparts in the real-world and the virtual environment, respectively. Results show the HE have similar performance when evaluating artefacts usability in VR and real-world in terms of identified usability problems. The VR implementation has an impact on the immersive VR evaluation result.

In 3D environments, objects can be difficult to select when they overlap, as this affects available target area and increases selection ambiguity. We introduce Outline Pursuits which extends a primary pointing modality for gaze-assisted selection of occluded objects. Candidate targets within a pointing cone are presented with an outline that is traversed by a moving stimulus. This affords completion of the selection by gaze attention to the intended target's outline motion, detected by matching the user's smooth pursuit eye movement. We demonstrate two techniques implemented based on the concept, one with a controller as the primary pointer, and one in which Outline Pursuits are combined with head pointing for hands-free selection. Compared with conventional raycasting, the techniques require less movement for selection as users do not need to reposition themselves for a better line of sight, and selection time and accuracy are less affected when targets become highly occluded.

TV experiences are often social, be it at-a-distance (through text) or in-person (through speech). Mixed Reality (MR) headsets offer new opportunities to enhance social communication during TV viewing by placing social artifacts (e.g. text) anywhere the viewer wishes, rather than being constrained to a smartphone or TV display. In this paper, we use VR as a test-bed to evaluate different text locations for MR TV specifically. We introduce the concepts of wall messages, below-screen messages, and egocentric messages in addition to state-of-the-art on-screen messages (i.e., subtitles) and controller messages (i.e., reading text messages on the mobile device) to convey messages to users during TV viewing experiences. Our results suggest that a) future MR systems that aim to improve viewers’ experience need to consider the integration of a communication channel that does not interfere with viewers’ primary task, that is watching TV, and b) independent of the location of text messages, users prefer to be in full control of them, especially when reading and responding to them. Our findings pave the way for further investigations towards social at-a-distance communication in Mixed Reality.