Prior work has shown that embodiment can benefit virtual agents, such as increasing rapport and conveying nonverbal information. However, it is unclear if users prefer an embodied to a speech-only agent for augmented reality (AR) headsets that are designed to assist users in completing real-world tasks. We conducted a study to examine users' perceptions and behaviors when interacting with virtual agents in AR. We asked 24 adults to wear the Microsoft HoloLens and find objects in a hidden object game while interacting with an agent that would offer assistance. We presented participants with four different agents: voice-only, non-human, full-size embodied, and a miniature embodied agent. Overall, users preferred the miniature embodied agent due to the novelty of his size and reduced uncanniness as opposed to the larger agent. From our results, we draw conclusions about how agent representation matters and derive guidelines on designing agents for AR headsets.
We found that cone dystrophy patients of all types had depressed rod-isolated ERGs across the board. If typical diagnostic criteria are used, these patients might be considered to have "abnormal" rod-isolated electroretinographic values, and might be called "cone-rod dystrophy", even though the waveforms are stable for years. Patients with cone-rod dysfunction patterns on ERG can be better understood by also performing kinetic (Goldmann) visual fields, which will help to distinguish cone dystrophies from progressive cone-rod dystrophies by central scotomata size and progression over time in many forms of cone-rod dystrophy.
Virtual agents are systems that add a social dimension to computing, often featuring not only natural language input but also an embodiment or avatar. This allows them to take on a more social role and leverage the use of nonverbal communication (NVC). In humans, NVC is used for many purposes, including communicating intent, directing attention, and conveying emotion. As a result, researchers have developed agents that emulate these behaviors. However, challenges pervade the design and development of NVC in agents. Some articles reveal inconsistencies in the benefits of agent NVC; others show signs of difficulties in the process of analyzing and implementing behaviors. Thus, it is unclear what the specific outcomes and effects of incorporating NVC in agents and what outstanding challenges underlie development. This survey seeks to review the uses, outcomes, and development of NVC in virtual agents to identify challenges and themes to improve and motivate the design of future virtual agents.
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