Standardized speech quality assessments should optimally occur in soundproof environments with minimal noise interference. However, poor ventilation in such environments can lead to increased CO2concentrations, which may affect cognitive function and judgement. This study investigates whether CO2levels affect speech quality ratings and response behaviour in listening tests. Across over 5,000 trials with 24 participants, we found three key effects: (1) higher CO2levels were associated with faster response times, indicating more impulsive decision-making; (2) ratings of poor-quality samples became more favorable, and high-quality samples less favorable under high CO2, suggesting reduced perceptual discrimination; (3) rating variability decreased, implying diminished sensitivity. These findings highlight a previously overlooked factor in speech quality research: ambient air quality may introduce bias into subjective ratings.

Traditional 2D video telephony systems often fail to convey critical non-verbal cues and spatial depth, limiting naturalistic remote communication and contributing to user fatigue. This study systematically investigates the experiential and interactive benefits of stereoscopic 3D video telephony compared to conventional 2D video calls. Thirty participants engaged in two communicative tasks—a free conversation and a game of Taboo—using a shutter-glasses-based stereoscopic setup and a matched 2D control. Measures included user satisfaction (UEQ), non-verbal immediacy (NIS-O), communication quality (audiovisual ratings, comfort, cognitive workload), and immersion (Film-IEQ). Results consistently demonstrated significantly higher user satisfaction, richer non-verbal communication, improved perceived audiovisual quality, and greater immersion in the 3D condition without increased cognitive workload or physical discomfort. These findings highlight the value of stereoscopic 3D video to enhance remote interpersonal interactions by providing depth cues that support more natural and engaging communication. The study contributes empirical evidence guiding the design and evaluation of emerging immersive telepresence technologies, offering a benchmark for future volumetric and point-cloud-based 3D communication systems.

The ability to establish eye contact is a central aspect of human communication and interaction. In video communication, however, it is impaired by the physical separation between camera and screen. This study investigates the effects of three video telephony configurations – standard video calls, teleprompter-assisted calls, and AI-based gaze correction – on user experience and perceived communication quality. In a collaborative task with 32 participants, we evaluated subjective dimensions such as Engagement, Naturalness of Eye Contact, and Social Presence across four conditions, including a face-to-face baseline. The results indicate that face-to-face interactions significantly outperform all video conditions in central dimensions. Notably, technical attempts to replicate natural eye contact, particularly through AI-based gaze correction, proved ineffective, leading to reduced perceived Naturalness of Eye Contact and increased Anxiety. These findings point to a heightened user sensitivity to artificial modifications in socially salient contexts. Although teleprompter-based solutions elicited less Anxiety, their technical constraints limit practical applicability. We conclude that current implementations of AI gaze correction, specifically the version in our study, are not yet suitable for enhancing conversational quality. Future efforts might benefit from focusing on design that build on the unique affordances of digital interaction, rather than aiming to replicate face-to-face dynamics.

Objectively measuring affective states remains a recurring challenge in psychology and user experience research. A promising proxy for perceived arousal is the momentary assessment of the pupil diameter. However, the pupillometric signal is highly susceptible to variations in stimulus luminance, which can substantially confound the results. We introduce a method to improve the accuracy of pupillometric signals as an arousal predictor by eliminating frame-by-frame luminance variations in visual stimuli (i.e. scaling the brightness value for all pixels such that each frame has the same average luminance). This process was termed "equalization". We tested our approach in a study with 31 participants between the ages of 21 and 64. Our study focused on two metrics: (1) the perceived quality of the stimuli should not be affected by the process, and (2) the predictive power of the pupillometric signal for the perceived arousal should be greater for the equalized videos than for the non-equalized ones. We used a within-subjects design, where each participant rated their affective response and five distinct quality dimensions of four videos (two in the equalized and two in the non-equalized condition). Our results indicate that the equalization process does improve the predictive power of the pupillometric signal by a substantial amount. Statistical analyses also show that the participants rated all quality dimensions equivalently for an equalized and non-equalized variant of the same stimulus, with only small differences that are limited to a subset of the perceptual dimensions. While potentially limiting the efficacy of the process in some scenarios, the strengthened explanatory power of the pupillometric signal leaves room for a wide range of possible applications.

While current Quality of Experience (QoE) formation models recognize the impact of user states on perception, they often overlook the subjective nuances and individual variations in these experiences. We discuss the integration of both situation-dependent and independent user states, show how dependent states are influenced by varying multimedia content quality, and reflect back into the QoE assessment. To address this gap, we conducted a comprehensive within-subjects lab study (N=92) in a video-telephony setting, employing variables representative of both dependent and independent states, such as affective states, social relationship, sympathy, and bodily needs. Dependent states were assessed per trial and independent states before or after the experiment. Our study investigates two key questions: How does video-telephony call quality influence user-dependent states, and how do both dependent and independent states collectively impact QoE ratings? Our findings reveal a substantial influence of call quality on user emotional states, underscoring the importance of considering these factors in QoE assessments. Moreover, a structural equation model comparison favored the dependent+independent state structure model, highlighting the significant impact of both independent and preceding dependent states on QoE ratings. This research advances QoE models by incorporating a more nuanced mental model of user states, leading to more personalized and accurate multimedia assessment tools, potentially enhancing users’ degree of delight or annoyance and engagement.

This study investigates the feasibility of remote virtual reality (VR) studies conducted at home using VR headsets and video conferencing by deploying an experiment on emotion ratings. 20 participants used head-mounted displays to immerse themselves in 360° videos selected to evoke emotional responses. The research compares continuous ratings using a graphical interface to retrospective questionnaires on a digitized Likert Scale for measuring arousal and valence, both based on the self-assessment manikin (SAM). It was hypothesized that the two different rating methods would lead to significantly different values for both valence and arousal. The goal was to investigate whether continuous ratings during the experience would better reflect users’ emotions compared to the post-questionnaire by mitigating biases such as the peak-end rule. The results show significant differences with moderate to strong effect sizes for valence and no significant differences for arousal with low to moderate effect sizes. This indicates the need for further investigation of the methods used to assess emotion ratings in VR studies. Overall, this study is an example of a remotely conducted VR experiment, offering insights into methods for emotion elicitation in VR by varying the timing and interface of the rating.

The EyeSight feature, introduced with the new Apple Vision Pro XR headset, promises to revolutionize user interaction by simulating real human eye expressions on a digital display. This feature could enhance XR devices’ social acceptability and social presence when communicating with others outside the XR experience. In this pilot study, we explore the implications of the EyeSight feature by examining social acceptability, social presence, emotional responses, and technology acceptance. Eight participants engaged in conversational tasks in three conditions to contrast experiencing the Apple Vision Pro with EyeSight, the Meta Quest 3 as a reference XR headset, and a face-to-face setting. Our preliminary findings indicate that while the EyeSight feature improves perceptions of social presence and acceptability compared to the reference headsets, it does not match the social connectivity of direct human interactions.

Estimating the quality of remote speech communication is a complex task influenced by the speaker, transmission channel, and listener. For example, the degradation of transmission quality can increase listeners’ cognitive load, which can influence the overall perceived quality of the conversation. This paper presents a framework that isolates quality-dependent changes and controls most outside influencing factors like personal preference in a simulated conversational environment. The performed statistical analysis finds significant relationships between stimulus quality and the listener’s valence and personality (agreeableness and openness) and, similarly, between the perceived task load during the listening task and the listener’s personality and frustration intolerance. The machine learning model of the task load prediction improves the correlation coefficients from 0.48 to 0.76 when listeners’ individuality is considered. The proposed evaluation framework and results pave the way for personalized audio quality assessment that includes speakers’ and listeners’ individuality beyond conventional channel modeling.

Preservation of private user data is of paramount importance for high Quality of Experience (QoE) and acceptability, particularly with services treating sensitive data, such as IT-based health services. Whereas anonymization techniques were shown to be prone to data re-identification, synthetic data generation has gradually replaced anonymization since it is relatively less time and resource-consuming and more robust to data leakage. Generative Adversarial Networks (GANs) have been used for generating synthetic datasets, especially GAN frameworks adhering to the differential privacy phenomena. This research compares state-of-the-art GAN-based models for synthetic data generation to generate time-series synthetic medical records of dementia patients which can be distributed without privacy concerns. Predictive modeling, autocorrelation, and distribution analysis are used to assess the Quality of Generating (QoG) of the generated data. The privacy preservation of the respective models is assessed by applying membership inference attacks to determine potential data leakage risks. Our experiments indicate the superiority of the privacy-preserving GAN (PPGAN) model over other models regarding privacy preservation while maintaining an acceptable level of QoG. The presented results can support better data protection for medical use cases in the future.

This manuscript investigates the suitability of video-based conversation simulations for studying human reactions to quality degradations, focusing on facial configurations as a proxy for QoE. We analyze data from two distinct studies: a video-simulated video-telephony scenario using the storytime dataset, where participants passively watched videos, and a second study involving real conversations between participants. In both studies, facial features were continuously recorded using Apple's iOS ARKit API. We identify a factor structure of facial features that significantly relates to participants' QoE ratings in the first study and validate its robustness by replicating it in the second, independent study. Our findings suggest statistically significant estimations of QoE ratings across both paradigms, demonstrating the suitability of passive conversation simulations for studying human reactions to quality degradation. We assess the value of the proposed approach at its present stage and conclude that it can be a valuable tool when used in conjunction with other methods, as its predictive capabilities are still not robust enough to rely solely on this analysis technique.

The subjective quality of experience (QoE) in multimedia contexts is influenced by various factors, including individual differences among raters and experimental setups. While the latter has been extensively studied, the former remains relatively unexplored. This paper investigates the impact of hangriness - a mental state of irritability and frustration caused by hunger - on QoE ratings. In our analysis, hangriness appears to be prevalent in a specific time interval, where individuals have not consumed any food between five and eleven hours. Our analysis, comprising ratings from 100 participants, reveals a significant, non-linear effect of hangriness on QoE ratings, specifically for multimedia stimuli with subpar quality. Participants in the hangry state rated such stimuli significantly worse compared to those who had eaten recently or abstained from food for more than eleven hours. Interestingly, this effect was not observed for high-quality multimedia content. Our findings highlight the importance of considering individual differences, such as hangriness, in QoE research, as they can significantly impact subjective ratings. Further research is needed to corroborate these results and explore other factors that may influence QoE ratings. This work contributes to a better understanding of individual variability in multimedia quality perception and provides insights for designing more reliable QoE assessment methods.

Nowadays, many apps use location data to estimate the user's behavior for targeted advertising, predicting significant locations, personal preferences, state of health, and sports activities. Users of location-based services are often left with no other choice than to accept or reject location tracking when they want to use various applications. Especially, users with higher privacy concerns may reduce the frequency of location tracking by turning it off in the settings. However, most users are unaware that many applications installed on their phones are continuously tracking them. Therefore, this study attempts to answer how (obviously) being tracked over one-week influences a user's privacy concerns. The study was implemented using an iOS app, which participants could install on their smartphones. Moreover, over one week, the participants were requested to answer daily mini-questionnaires about how much they would be willing to pay for the protection of their location information on a monthly basis and how much money they were willing to accept in exchange for their location information. Hereby, the context was an important criterion to determine how the monetary values vary among different location types for, among others, home location, work location, and meeting family and friends. The participants (N=51) interacted with the app on a daily basis by filling out various daily mini-surveys based on their significant locations visited. The results show a significant difference between the monetary valuating of willingness to pay and to accept for all location types except work location and sharing scenarios contributing to further empirical evidence for the endowment effect. The obvious fact of continuously being tracked did not increase the privacy concern of participants.

To study people's natural behavior during different conditions of audiovisual quality, we usually invite people into a lab and let them talk to each other. In such conversation settings, not only the media quality impacts the quality perception, but, e.g., social aspects of a real conversation are reflected by individual conversational and rating behavior. Hence, to study quality perception in conversational settings, we try to create an environment that isolates the media quality from such outside factors and is consistent for each participant in the lab. Therefore, we created a dataset of simulated videotelephony clips to act as stimuli in quality perception research. The dataset consists of four different stories in the German language that are told through ten consecutive parts, each about 10 seconds long. Each of these parts is available in four different quality levels, ranging from perfect to stalling. All clips (FullHD, H.264 / AAC) are actual recordings from end-user video-conference software to ensure ecological validity and realism of quality degradation. To ensure consistency among different clips of the same quality level, each video has been scored using VMAF and POLQA and selected to match predefined selection criteria. To analyze the perceived quality of the clips, we conducted a user study (N=25) and evaluated perceived quality, interest in the stories, and speaker engagement. Results validate the consistency of the quality levels of the video clips. Apart from a detailed description of the methodological approach, we contribute the entire stimuli dataset containing 160 videos and all rating scores for each file.

Over the past five years, the interest in Augmented Reality (AR) technologies has significantly increased. Different industries adopted it, such as gaming, tourism, e-commerce, and entertainment, to name a few. Due to its non-fully immersive property, easy implementation, and compatibility with the most recent smartphones, AR seems to be suitable for daily usage. This poses a significant challenge in creating a good User Experience (UX), as this kind of technology needs to be designed for private scenarios and public ones. In its context, it is essential to understand how users are influenced in their social interactions while using AR. Through the use of humanoid Virtual Characters, this paper is intended to better the understanding of how people perceive personal space in AR. By varying Virtual Character Gender (male, female) and its Placement Modality (predefined, dynamic distance) in the real environment, the effects on UX, Emotions, and Social Presence are investigated. As Personal Space is a dynamic psychological construct, which could depend on individual factors, this paper further investigates some possible co-variant effects of users' preferences towards a female or a male character based on their Sexual Attraction. Results show that Placement Modality significantly affects Personal Space boundaries in terms of position, width, and hedonic quality of the experience. Moreover, an effect of Virtual Character Gender was found on users' Personal Space inner boundary, and Social Presence in its emotional contagion dimension. Finally, an effect of Sexual Attraction on UX, Social Presence in its emotional contagion dimension, and dominance were discovered.

Touch interaction has established a dominating role in the realisation of Human–Machine Interfaces. However, to be able to use touch effectively and efficiently, users have to comply with particular prerequisites. Due to age-related changes, such as the decline of tactile accuracy and speed, especially elderly users often struggle with the touch modality. Interfaces that adapt to specific user characteristics could be a promising solution to overcome this problem. Notwithstanding the advantages of adaptive systems, perceived changes in the user interface can reduce the system's predictability and transparency. The present study compares three approaches concerning the adaptation of touch button sizes: no adaptation and adaptation with visible and invisible feedback. Results show that especially elderly users substantially benefit from an adaptive approach. Furthermore, data shows that the type of adaptation supports different usage goals. While adaption with visual feedback enables a higher interaction speed, invisible adaptation leads to a higher degree of accuracy.

The COVID-19 pandemic has induced dramatic effects in all areas of society worldwide. It has led to drastic restrictions on academic exchanges and caused research projects to be put on hold. The need to maintain social distancing has severely affected the research communities that rely on in-person studies. In particular, Quality of Experience (QoE) research relies heavily on user studies and in-person subjective tests as means of obtaining ground truths for system designs. In this position paper, we focus on the impact of COVID-19 on conducting subjective tests for digital media quality assessment. An overview of the related discussions that take place in associated research communities is provided. A number of challenges are posed in terms of hygiene, ethics, standardization, and research quality issues. Opportunities for consolidating QoE research under COVID-19 and beyond are put forward, including alternative experimental designs and adaptation of research methodologies. Numerous enablers are suggested and discussed, revealing various avenues that can be followed to assist in conducting subjective tests under pandemic conditions. We believe that this position paper will be helpful for researchers and practitioners relying on in-person studies to keep abreast about the potential measures that support coming out of the COVID-19 pandemic strong and being prepared for future endeavors.

Advancing technology and higher availability of Virtual Reality (VR) devices sparked its application in various research fields. For instance, health-related research showed that simulated nature environments in VR could reduce arousal and increase valence levels. This study investigates how the amount of possible interactivity influences the presence in nature environments and consequences on arousal and valence. After inducing fear (high arousal and low valence) through a VR-horror game, it was tested how participants recovered if they played a VR-nature game with either no, limited, or extensive interaction. The horror game proved to be a valid stimulus for inducing high arousal and low valence with a successful manipulation check. Igroup presence questionnaire (IPQ) scores showed that more interaction with the virtual environment increases spatial presence. A beneficial effect of experiencing nature can also be concluded. Results from the Self-Assessment Manikin questionnaire (SAM) scores for valence indicate a significant increase in the conditions with extensive and limited interaction compared to the control group. The VR Nature experience did significantly decrease arousal and increase valence compared to the post-horror game ratings. The physiological responses support this finding. These results can increase the effectiveness of health-related VR-applications to elevate mood levels by either implementing plenty of interactions and consequently increasing spatial presence or doing the opposite and leaving out any interactions at all.

Combining interconnected wearables provides fascinating opportunities like augmenting exergaming with virtual coaches, feedback on the execution of sports activities, or how to improve on them. Breathing rhythm is a particularly interesting physiological dimension since it is easy and unobtrusive to measure and gained data provide valuable insights regarding the correct execution of movements, especially when analyzed together with additional movement data in real-time. In this work, we focus on indoor rowing since it is a popular sport that's often done alone without extensive instructions. We compare a visual breathing indication with haptic guidance in order for athletes to maintain a correct, efficient, and healthy breathing-movement-synchronicity (BMS) while working out. Also, user experience and acceptance of the different modalities were measured. The results show a positive and statistically significant impact of purely verbal instructions and purely tactile feedback on BMS and no significant impact of visual feedback. Interestingly, the subjective ratings indicate a strong preference for the visual modality and even an aversion for the haptic feedback, although objectively the performance benefited most from using the latter.

Virtual Reality (VR) has an increasing impact on the market in many fields, from education and medicine to engineering and entertainment, by creating different applications that replicate or in the case of augmentation enhance real-life scenarios. Intending to present realistic environments, VR applications are including text that we are surrounded by every day. However, text can only add value to the virtual environment if it is designed and created in such a way that users can comfortably read it. With the aim to explore what values for text parameters users find comfortable while reading in virtual reality, a study was conducted allowing participants to manipulate text parameters such as font size, distance, and contrast. Therefore two different standalone virtual reality devices were used, Oculus Go and Quest, together with three different text samples: Short (2 words), medium (21 words), and long (51 words). Participants had the task of setting text parameters to the best and worst possible value. Additionally, participants were asked to rate their experience of reading in virtual reality. Results report mean values for angular size (the combination of distance and font size) and color contrast depending on the different device used as well as the varying text length, for both tasks. Significant differences were found for values of angular size, depending on the length of the displayed text. However, different device types had no significant influence on text parameters but on the experiences reported using the self-assessment manikin (SAM) scale.