Eye typing is a hands-free method of human computer interaction, which is especially useful for people with upper limb disabilities. Users select a desired key by gazing at it in an image of a keyboard for a fixed dwell time. There is a tradeoff in selecting the dwell time; shorter dwell times lead to errors due to unintentional selections, while longer dwell times lead to a slow input speed. We propose to speed up eye typing while maintaining low error by dynamically adjusting the dwell time for each letter based on the past input history. More likely letters are assigned shorter dwell times. Our method is based on a probabilistic generative model of gaze, which enables us to assign dwell times using a principled model that requires only a few free parameters. We evaluate our model on both able-bodied subjects and subjects with a spinal cord injury (SCI). Compared to the standard dwell time method, we find consistent increases in typing speed in both cases. e.g., 41.8% faster typing for able-bodied subjects on a transcription task and 49.5% faster typing for SCI subjects in a chatbot task. We observed more inter-subject variability for SCI subjects.

中文翻译：

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动态贝叶斯调整停留时间以加快眼睛打字速度

眼睛打字是人机交互的一种免提方法，对上肢残疾的人特别有用。用户通过在键盘图像中凝视所需的键并保持固定的停留时间来选择所需的键。选择停留时间需要权衡；较短的停留时间会由于意外选择而导致错误，而较长的停留时间则会导致输入速度变慢。我们建议根据过去的输入历史记录动态调整每个字母的停留时间，从而在保持低错误的同时加快眼睛打字速度。分配给更多可能字母的停留时间更短。我们的方法基于凝视的概率生成模型，该模型使我们能够使用仅需要几个自由参数的原理模型来分配停留时间。我们评估身体健康的受试者和脊髓损伤（SCI）受试者的模型。与标准的驻留时间方法相比，我们发现在两种情况下打字速度都持续提高。例如，在转录任务中，健全主体的打字速度快41.8％，在聊天机器人任务中SCI主体的打字速度快49.5％。我们观察到SCI受试者的受试者间差异更大。