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

被引:14
|
作者
Zhao, Maozheng [1 ]
Huang, Henry [2 ]
Li, Zhi [1 ]
Liu, Rui [1 ]
Cui, Wenzhe [1 ]
Toshniwal, Kajal [1 ]
Goel, Ananya [1 ]
Wang, Andrew [3 ]
Zhao, Xia [4 ]
Rashidian, Sina [5 ]
Baig, Furqan [6 ]
Phi, Khiem [1 ]
Zhai, Shumin
Ramakrishnan, I. V. [1 ]
Wang, Fusheng [1 ]
Bi, Xiaojun [1 ]
机构
[1] SUNY Stony Brook, Dept Comp Sci, Stony Brook, NY 11794 USA
[2] Tappan Zee High Sch, Orangeburg, NY USA
[3] Ward Melville High Sch, East Setauket, NY USA
[4] Stony Brook Med, Stony Brook, NY USA
[5] Verily Life Sci, Cambridge, MA USA
[6] Univ Illinois, Urbana, IL USA
基金
美国国家科学基金会;
关键词
multiniodal interaction; eye gaze; text correction; voice input;
D O I
10.1145/3490099.3511103
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:470 / 482
页数:13
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