@inproceedings{b387c5003deb464e814d2639b778533a,
title = "LipText: Lip Tracking Based Text Entry in VR",
abstract = "Text entry is an important task in virtual reality (VR), and most existing methods require hand involvement, while hands-free typing has great potential for applications in mobile scenarios. Existing hands-free text entry methods are usually implemented by combining the head and eyes with techniques such as Dwell, Blink and Gesture, which can easily fatigue the user. In this paper, we propose LipText, a lip-tracking-based text entry method in VR. We use a neural network to perform letter-level prediction on the lip data captured by the facial tracker and use head-based selection as an auxiliary to improve the accuracy. We conduct a user study to evaluate our method, the results show a typing speed of 8.63 WPM for the novice group, 9.81 WPM for the potential expert group, and the highest recorded typing speed is 11.13 WPM achieved by a potential expert. Our method is also novice-friendly, and their typing speed increased by 64.38\% over a six-day practice.",
keywords = "Hands-free, Text entry, Virtual reality",
author = "Jiaye Leng and Zijun Wang and Jian Wu and Lili Wang",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; 1st International Conference on Extended Reality, ICXR 2024 ; Conference date: 14-11-2024 Through 17-11-2024",
year = "2025",
doi = "10.1007/978-981-96-3679-2\_11",
language = "英语",
isbn = "9789819636785",
series = "Lecture Notes in Computer Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "162--178",
editor = "Weitao Song and Frank Guan and Shuai Li and Guofeng Zhang",
booktitle = "Extended Reality - 1st International Conference, ICXR 2024, Proceedings",
address = "德国",
}