As camouflaged targets share visual characteristics with the environment within which they are embedded, searchers rarely have access to a perfect visual template of such targets. Instead, they must rely on less specific representations to guide search. Although search for camouflaged and non-specified targets have both received attention in the literature, to date they have not been explored in a combined context. Here we introduce a new paradigm for characterizing behavior during search for camouflaged targets in natural scenes, while also exploring how the fidelity of the target template affects search processes. Search scenes were created from forest images, with targets a distortion (varied size) of that image at a random location. In Experiment 1 a preview of the target was provided; in Experiment 2 there was no preview. No differences were found between experiments on nearly all measures. Generally, reaction times and accuracy improved with familiarity on the task (more so for small targets). Analysis of eye movements indicated that performance benefits were related to improvements in both Search and Target Verification time. Combined, our data suggest that search for camouflaged targets can be improved over a short time-scale, even when targets are poorly defined.
Until recently, designing the interactions between systems and users has relied primarily on visual communication. However, with the dramatic increase in the use of virtual assistants, voice interaction design is now a sought after skill for human factors and user experience practitioners. In this practice-oriented paper, we aim to identify the best practices for dialog designers striving to minimize errors in communication between the user and the voice-enabled system. Furthermore, we highlight the technology behind voice systems as well as the importance of minimizing errors when our voice-controlled devices become a part of highly sensitive interactions: specifically, when accessing critical, private information. Summary: This is a practice-oriented paper highlighting six best practices for avoiding errors when designing voice-enabled systems. Errors in voice systems have been found to require a great deal of user effort to resolve, as well as strongly influence user satisfaction with their voice system. We discuss the technical foundation for voice user interfaces (VUIs) as well as the evolving nature of these systems. The purpose of this paper is to aid and inform upcoming voice design practitioners in the best method for dialog designing.
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