EyeSayCorrect: Eye Gaze and Voice Based Hands-free Text Correction for Mobile Devices

EyeSayCorrect: Eye Gaze and Voice Based Hands-free Text Correction for Mobile Devices
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EyeSayCorrect:适用于移动设备的基于眼睛注视和语音的免提文本校正

DOI:
10.1145/3490099.3511103
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发表时间:
2022
期刊:
IUI '22: 27th International Conference on Intelligent User Interfaces
影响因子:
--
通讯作者:
Rashidian, Sina
Rashidian, Sina
中科院分区:
--
文献类型:
--
作者:
Zhao, Maozheng;Huang, Henry;Li, Zhi;Liu, Rui;Cui, Wenzhe;Toshniwal, Kajal;Goel, Ananya;Wang, Andrew;Zhao, Xia;Rashidian, Sina

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移动的设备上的文本校正通常需要精确和重复的手动控制。在本文中,我们提出了EyeSayCorrect,眼睛注视和语音为基础的免提文本校正方法的移动的设备。要使用EyeSayCorrect纠正文本,用户首先利用屏幕上的注视位置来选择一个单词,然后说出新短语。然后,EyeSayCorrect将基于输入和文本上下文来推断用户的校正意图。我们使用贝叶斯方法来确定所选择的词给定的眼睛注视轨迹。给定眼睛注视轨迹中的每个采样点,计算并累积选择单词的后验概率。当目标词的累积兴趣大于阈值时,选择目标词。拼写错误的单词有更高的优先级。我们的用户研究表明,使用先验的拼写错误的单词减少任务完成时间高达23.79%和文本选择时间高达40.35%,和EyeSayCorrect是一个可行的免提文本校正方法在移动的设备。
Text correction on mobile devices usually requires precise and repetitive manual control. In this paper, we present EyeSayCorrect, an eye gaze and voice based hands-free text correction method for mobile devices. To correct text with EyeSayCorrect, the user first utilizes the gaze location on the screen to select a word, then speaks the new phrase. EyeSayCorrect would then infer the user’s correction intention based on the inputs and the text context. We used a Bayesian approach for determining the selected word given an eye-gaze trajectory. Given each sampling point in an eye-gaze trajectory, the posterior probability of selecting a word is calculated and accumulated. The target word would be selected when its accumulated interest is larger than a threshold. The misspelt words have higher priors. Our user studies showed that using priors for misspelt words reduced the task completion time up to 23.79% and the text selection time up to 40.35%, and EyeSayCorrect is a feasible hands-free text correction method on mobile devices.
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