Alnfiai Mrim M, Kabir Muhammad Ashad
Department of Information Technology, College of Computers and Information Technology, Taif University, Taif, 21944, Saudi Arabia.
School of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW, 2795, Australia.
Heliyon. 2024 Aug 23;10(17):e36653. doi: 10.1016/j.heliyon.2024.e36653. eCollection 2024 Sep 15.
Assistive technologies have been developed to enhance blind users' typing performance, focusing on speed, accuracy, and effort reduction. One such technology is word prediction software, designed to minimize keystrokes required for text input. This study investigates the impact of word prediction on typing performance among blind users using an on-screen QWERTY keyboard. We conducted a comparative study involving eleven blind participants, evaluating both standard QWERTY input and word prediction-assisted typing. Our findings reveal that while word prediction slightly improves typing speed, it does not enhance typing accuracy and increases both physical and temporal workload compared to the default keyboard. We conclude with recommendations for improving word prediction systems, including more efficient editing methods and the integration of voice pitch variations to aid error recognition.
已经开发出辅助技术来提高盲人用户的打字性能，重点是速度、准确性和减少工作量。其中一项技术是单词预测软件，旨在最大限度地减少文本输入所需的击键次数。本研究调查了单词预测对使用屏幕QWERTY键盘的盲人用户打字性能的影响。我们进行了一项比较研究，涉及11名盲人参与者，评估了标准QWERTY输入和单词预测辅助打字。我们的研究结果表明，虽然单词预测略微提高了打字速度，但与默认键盘相比，它并没有提高打字准确性，反而增加了身体和时间上的工作量。我们最后提出了改进单词预测系统的建议，包括更有效的编辑方法以及整合音高变化以帮助错误识别。
