Torsten W. Kuhlen’s research while affiliated with RWTH Aachen University and other places

Collaborative work in large virtual environments often requires transitions from loosely-coupled collaboration at different locations to tightly-coupled collaboration at a common meeting point. Inspired by prior work on the continuum between these extremes, we present two novel interaction techniques designed to share spatial context while collaborating over large virtual distances. The first method replicates the familiar setup of a video conference by providing users with a virtual tablet to share video feeds with their peers. The second method called PASCAL (Parallel Avatars in a Shared Collaborative Aura Link) enables users to share their immediate spatial surroundings with others by creating synchronized copies of it at the remote locations of their collaborators. We evaluated both techniques in a within-subject user study, in which 24 participants were tasked with solving a puzzle in groups of two. Our results indicate that the additional contextual information provided by PASCAL had significantly positive effects on task completion time, ease of communication, mutual understanding, and co-presence. As a result, our insights contribute to the repertoire of successful interaction techniques to mediate between loosely- and tightly-coupled work in collaborative virtual environment

Listening to conversations and remembering their content is a highly demanding task, especially in noisy environments. Previous research has mainly focused on short-term memory using simple cognitive tasks with unrelated words or digits. The present study investigates the listeners’ short-term memory and listening effort in conversations under different listening conditions, with and without soft or moderate noise. To this end, participants were administered a dual-task paradigm, including a primary listening task, in which conversations between two talkers were presented, and an unrelated secondary task. In Experiment 1, this secondary task was a visual number-judgment task, whereas in Experiments 2 and 3, it was a vibrotactile pattern recognition task. All experiments were conducted in a quiet environment or under continuous broadband noise. For the latter, the signal-to-noise ratio in Experiments 1 and 2 was +10 dB (soft-noise condition), while in Experiment 3 it was -3 dB (moderate-noise condition). In Experiments 1 and 2, short-term memory of running speech and listening effort were unaffected by soft-noise listening conditions. In Experiment 3, however, the moderate-noise listening condition impaired performance in the primary listening task, while performance in the vibrotactile secondary task was unaffected. This pattern of results could suggest that the moderate-noise listening condition, with a signal-to-noise ratio of -3 dB, required increased listening effort compared to the soft-noise and quiet listening conditions. These findings indicate that listening situations with moderate noise can reduce short-term memory of heard conversational content and increase listening effort, even when the speech signals remain highly intelligible.

One core aspect of immersive visualization labs is to develop and provide powerful tools and applications that allow for efficient analysis and exploration of scientific data. As the requirements for such applications are often diverse and complex, the same applies to the development process. This has led to a myriad of different tools, frameworks, and approaches that grew and developed over time. The steady advance of commercial off-the-shelf game engines such as Unreal Engine has made them a valuable option for development in immersive visualization labs. In this work, we share our experience of migrating to Unreal Engine as a primary developing environment for immersive visualization applications. We share our considerations on requirements, present use cases developed in our lab to communicate advantages and challenges experienced, discuss implications on our research and development environments, and aim to provide guidance for others within our community facing similar challenges.

Virtual reality (VR) environments are frequently used in auditory and cognitive research to imitate real-life scenarios, presumably enhancing state-of-the-art approaches with traditional computer screens. However, the effects of different display technologies on audiovisual processing remain underexplored. This study investigated how VR displayed with an head-mounted display (HMD) affects serial recall performance compared to traditional computer monitors, focusing on their effects on audiovisual processing in cognitive tasks. For that matter, we conducted two experiments with both an HMD and a computer monitor as display devices and two types of audiovisual incongruences: angle (Exp. 1) and voice (Exp. 2) incongruence. To quantify cognitive performance an audiovisual verbal serial recall (avVSR) task was developed where an embodied conversational agent (ECA) was animated to speak the target digit sequence. Even though subjective evaluations showed a higher sense of presence in the HMD condition, we found no effect of the display device on the proportion of correctly recalled digits. For the extreme conditions of angle incongruence in the computer monitor presentation the proportion of correctly recalled digits increased marginally, presumably due to raised attention, but the effect is likely too small to be meaningful. Response times were not affected by incongruences in either display device across both experiments. These findings suggest that the avVSR task is robust against angular and voice audiovisual incongruences, irrespective of the display device, at least for the conditions studied here. Hence, the study introduces the avVSR task in VR and contributes to the understanding of audiovisual integration.

We present a data acquisition and visualization pipeline that allows experts to monitor additive manufacturing processes, in particular laser metal deposition with wire (LMD-w) processes, in immersive virtual reality. Our virtual environment consists of a digital shadow of the LMD-w production site enriched with additional measurement data shown on both static as well as handheld virtual displays. Users can explore the production site by enhanced teleportation capabilities that enable them to change their scale as well as their elevation above the ground plane. In an exploratory user study with 22 participants, we demonstrate that our system is generally suitable for the supervision of LMD-w processes while generating low task load and cybersickness. Therefore, it serves as a first promising step towards the successful application of virtual reality technology in the comparatively young field of additive manufacturing.

Many lecturers develop voice problems, such as hoarseness. Nevertheless, research on how voice quality influences listeners’ perception, comprehension, and retention of spoken language is limited to a small number of audio-only experiments. We aimed to address this gap by using audio-visual virtual reality (VR) to investigate the impact of a lecturer’s hoarseness on university students’ heard text recall, listening effort, and listening impression. Fifty participants were immersed in a virtual seminar room, where they engaged in a Dual-Task Paradigm. They listened to narratives presented by a virtual female professor, who spoke in either a typical or hoarse voice. Simultaneously, participants performed a secondary task. Results revealed significantly prolonged secondary-task response times with the hoarse voice compared to the typical voice, indicating increased listening effort. Subjectively, participants rated the hoarse voice as more annoying, effortful to listen to, and impeding for their cognitive performance. No effect of voice quality was found on heard text recall, suggesting that, while hoarseness may compromise certain aspects of spoken language processing, this might not necessarily result in reduced information retention. In summary, our findings underscore the importance of promoting vocal health among lecturers, which may contribute to enhanced listening conditions in learning spaces.

One core aspect of immersive visualization labs is to develop and provide powerful tools and applications that allow for efficient analysis and exploration of scientific data. As the requirements for such applications are often diverse and complex, the same applies to the development process. This has led to a myriad of different tools, frameworks, and approaches that grew and developed over time. The steady advance of commercial off-the-shelf game engines such as Unreal Engine has made them a valuable option for development in immersive visualization labs. In this work, we share our experience of migrating to Unreal Engine as a primary developing environment for immersive visualization applications. We share our considerations on requirements, present use cases developed in our lab to communicate advantages and challenges experienced, discuss implications on our research and development environments, and aim to provide guidance for others within our community facing similar challenges.