Our results are consistent with previous work in VR and optical see-through (OST) AR, but additionally provide novel insights into usability and performance of the selected text input techniques for VST AR. Participants showed a significant learning effect with only ten sentences typed per condition. Further, the tap keyboard was significantly faster than the swipe keyboard in VR. ![]() In terms of performance, both input techniques were significantly faster in VR than in VST AR. Task load was also lower for tap keyboards. We found significantly higher usability and user experience ratings for tap keyboards compared to swipe keyboards in both VR and VST AR. A user evaluation with 64 participants revealed that XR displays and input techniques strongly affect text entry performance, while subjective measures are only influenced by the input techniques. The developed contact-based mid-air virtual tap and wordgesture (swipe) keyboard provide established support functions for text correction, word suggestions, capitalization, and punctuation. This article compares two state-of-the-art text input techniques between non-stationary virtual reality (VR) and video see-through augmented reality (VST AR) use-cases as XR display condition. However, on the two large datasets, the deep learning approach performs better (22.9%& 28.07% for Scaled Manhattan / 12.25% & 20.74% for ITAD versus 0.93% & 6.77% for TypeNet). Our results show that on the small dataset, statistical algorithms significantly outperformthe deep learning approach (Equal Error Rate (EER) of 4.3% for Scaled Manhattan / 1.3% for ITAD versus19.18% for TypeNet). ![]() When shouldstatistical algorithms be preferred over deep learning and vice-versa? To answer this question, we set up ex-periments to evaluate two state-of-the-art statistical algorithms: Scaled Manhattan and the Instance-based TailArea Density (ITAD) metric, with a state-of-the-art deep learning model called TypeNet, on three datasets (onesmall and two large). ![]() However, deeplearning has recently started to gain popularity due to their ability to achieve better performance. Statistical algorithms such as distance measures have long been a com-mon choice for keystroke authentication due to their simplicity and ease of implementation. Keystroke dynamics has gained relevance over the years for its potential in solving practical problems likeonline fraud and account takeovers.
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