Implications of the uncanny valley of avatars and virtual characters for human-computer interaction

Technological innovations made it possible to create more and more realistic figures. Such figures are often created according to human appearance and behavior allowing interaction with artificial systems in a natural and familiar way. In 1970, the Japanese roboticist Masahiro Mori observed, however, that robots and prostheses with a very - but not perfect - human-like appearance can elicit eerie, uncomfortable, and even repulsive feelings. While real people or stylized figures do not seem to evoke such negative feelings, human depictions with only minor imperfections fall into the "uncanny valley," as Mori put it. Today, further innovations in computer graphics led virtual characters into the uncanny valley. Thus, they have been subject of a number of disciplines. For research, virtual characters created by computer graphics are particularly interesting as they are easy to manipulate and, thus, can significantly contribute to a better understanding of the uncanny valley and human perception. For designers and developers of virtual characters such as in animated movies or games, it is important to understand how the appearance and human-likeness or virtual realism influence the experience and interaction of the user and how they can create believable and acceptable avatars and virtual characters despite the uncanny valley. This work investigates these aspects and is the next step in the exploration of the uncanny valley. This dissertation presents the results of nine studies examining the effects of the uncanny valley on human perception, how it affects interaction with computing systems, which cognitive processes are involved, and which causes may be responsible for the phenomenon. Furthermore, we examine not only methods for avoiding uncanny or unpleasant effects but also the preferred characteristics of virtual faces. We bring the uncanny valley into context with related phenomena causing similar effects. By exploring the eeriness of virtual animals, we found evidence that the uncanny valley is not only related to the dimension of human-likeness, which significantly change our view on the phenomenon. Furthermore, using advanced hand tracking and virtual reality technologies, we discovered that avatar realism is connected to other factors, which are related to the uncanny valley and depend on avatar realism. Affinity with the virtual ego and the feeling of presence in the virtual world were also affected by gender and deviating body structures such as a reduced number of fingers. Considering the performance while typing on keyboards in virtual reality, we also found that the perception of the own avatar depends on the user's individual task proficiencies. This thesis concludes with implications that not only extends existing knowledge about virtual characters, avatars and the uncanny valley but also provide new design guidelines for human-computer interaction and virtual reality

The uncanny valley of a virtual animal.

Virtual robots, including virtual animals, are expected to play a major role within affective and aesthetic interfaces, serious games, video instruction, and the personalization of educational instruction. Their actual impact, however, will very much depend on user perception of virtual characters as the uncanny valley hypothesis has shown that the design of virtual characters determines user experiences. In this article, we investigated whether the uncanny valley effect, which has already been found for the human-like appearance of virtual characters, can also be found for animal-like appearances. We conducted an online study (N = 163) in which six different animal designs were evaluated in terms of the following properties: familiarity, commonality, naturalness, attractiveness, interestingness, and animateness. The study participants differed in age (under 10–60 years) and origin (Europe, Asia, North America, and South America). For the evaluation of the results, we ranked the animal-likeness of the character using both expert opinion and participant judgments. Next to that, we investigated the effect of movement and morbidity. The results confirm the existence of the uncanny valley effect for virtual animals, especially with respect to familiarity and commonality, for both still and moving images. The effect was particularly pronounced for morbid images. For naturalness and attractiveness, the effect was only present in the expert-based ranking, but not in the participant-based ranking. No uncanny valley effect was detected for interestingness and animateness. This investigation revealed that the appearance of virtual animals directly affects user perception and thus, presumably, impacts user experience when used in applied settings

Giving robots a voice: human-in-the-loop voice creation and open-ended labeling

Speech is a natural interface for humans to interact with robots. Yet, aligning a robot’s voice to its appearance is challenging due to the rich vocabulary of both modalities. Previous research has explored a few labels to describe robots and tested them on a limited number of robots and existing voices. Here, we develop a robot-voice creation tool followed by large-scale behavioral human experiments (N=2,505). First, participants collectively tune robotic voices to match 175 robot images using an adaptive human-in-the-loop pipeline. Then, participants describe their impression of the robot or their matched voice using another human-in-the-loop paradigm for open-ended labeling. The elicited taxonomy is then used to rate robot attributes and to predict the best voice for an unseen robot. We offer a web interface to aid engineers in customizing robot voices, demonstrating the synergy between cognitive science and machine learning for engineering tools

Application of Virtual Reality in the study of Human Behavior in Fire : Pursuing realistic behavior in evacuation experiments

Virtual Reality (VR) experiments are used to study human behavior in fire because they allow simulation of fire events with relatively low risks to the participants, while maintaining high levels of experimental control. Manystudies have used VR experiments to explore aspects of the human response to fire threats, but VR experiments as a research method are yet to be subjected to a systematic process of validation. One way to validate VR experiments is to compare VR data to data obtained using other research methods, e.g., case studies, laboratory experiments, and field experiments. Five independent VR experiments were designed to collect data that could be then compared to data collected using other research methods. Both datasets, VR and physical, are thencompared with each other to assess similarities and differences between them. Results show that participants in the VR experiments often acted like people did in the physical-world events. Moreover, Human Behavior in Fire theories that explain the behavior of victims in real fires were found to also explain the participants’ behavior in the VR experiments. There were differences between VR and physical-world samples, which highlighted limitations of VR experiments or aspects about realism that need to be considered when designing VR experiments. Visual realism is not enough for participants to interpret a virtual fire emergency as a threat. Therefore, VR experiments need to induce participants to take the virtual fire event seriously. Social norms that apply in physical world contexts may not emerge naturally in virtual environments, and measures should be taken to enhance behavioral realism in VR. These findings are a meaningful contribution to the development of the VR experiment method for collection of behavioral data