Life in the Fast Lane: Effect of Language and Calibration Accuracy on the Speed of Text Entry by Gaze

Räihä, Kari-Jouko

doi:10.1007/978-3-319-22701-6_30

Cited by 10 publications

(13 citation statements)

References 15 publications

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“…Participants with glasses (5 out of 10) experienced calibration problems, which affected their usage of dwell-time typing, as expected according to Räihä [17]. Our statistically limited analysis suggests that EyeSwipe may be more robust to noisy gaze data associated with people wearing glasses.…”

Section: Typing Ratesupporting

confidence: 60%

EyeSwipe

Kurauchi

Feng

Joshi

et al. 2016

Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

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Text entry using gaze-based interaction is a vital communication tool for people with motor impairments. Most solutions require the user to fixate on a key for a given dwell time to select it, thus limiting the typing speed. In this paper we introduce EyeSwipe, a dwell-time-free gaze-typing method. With EyeSwipe, the user gaze-types the first and last characters of a word using the novel selection mechanism "reverse crossing." To gaze-type the characters in the middle of the word, the user only needs to glance at the vicinity of the respective keys. We compared the performance of EyeSwipe with that of a dwell-time-based virtual keyboard. EyeSwipe afforded statistically significantly higher typing rates and more comfortable interaction in experiments with ten participants who reached 11.7 words per minute (wpm) after 30 min typing with EyeSwipe.

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Section: Typing Ratesupporting

confidence: 60%

EyeSwipe

Kurauchi

Feng

Joshi

et al. 2016

Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems

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“…User satisfaction, assessed with SUS can be described as usable [27]. However, for the previous findings, it has to be pointed out, that the comparability between studies on gaze-based interaction may be limited by between study factors such as accuracy of tracking or the sample of users [28]. Thus, in order to give a more stable estimation of the performance of this selection mechanism, a comparative dwell-time baseline condition is needed and should be addressed as a next step.…”

Section: Discussionmentioning

confidence: 99%

Towards Pupil-Assisted Target Selection in Natural Settings: Introducing an On-Screen Keyboard

Strauch¹,

Greiter²,

Huckauf³

2017

Human-Computer Interaction – INTERACT 2017

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Preliminary reports have shown the possibility to assist input commands in HCI via pupil dilation. Applicability of these findings is however subject to further investigations, since the specificity of changes in diameter is low, e.g. through variations in brightness. Investigating employability and shape of pupil size dynamics outside a strictly controlled laboratory, we implemented the emulation of selection via an integrated mechanism of pupil dilation and constriction that could speed up a dwell time of 1.5 s. During the operation of an onscreen keyboard, 21 subjects were able to type via this mechanism, needing 1 s on average per keystroke and producing only slightly more than 1% false positive selections. Hereby, pupil dynamics were assessed. More than 90% of keystrokes could be accelerated under assistance of pupil variations. As suggested from basic research, pupil dilated when fixating later selected keys and constricted shortly afterwards. This finding was consistent between all subjects, however, pupil dynamics were shifted in regard to temporal occurrence and amplitude of diameter changes. Pupil-Assisted Target Selection shows potential in non-strictly controlled environments for computer input and may be further improved on the basis of this data. This might culminate in an integrated gaze-based object selection mechanism that could go beyond the benchmarking dwell time performance.

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“…A virtual keyboard 12 [Räihä 2015] layout included 29 letters of Finnish language, punctuation marks and additional controls: SPACE, BACKSPACE and READY (as illustrated in Fig. 1).…”

Section: Virtual Keyboardmentioning

confidence: 99%

“…Hands-free text entry by means of voluntarily produced and controlled gestures and movements of eyes, face and head has received special attention in the research community. Thus, writing electronic texts with gaze-controlled VBIs (g-VBIs), socalled eye typing, has been thoroughly studied [Majaranta 2012;Majaranta and Räihä 2007;Räihä 2015]. Eye typing often involves gazing at a key of a virtual keyboard and dwelling the gaze on that key for about 1 s in order to activate it.…”

Section: Introductionmentioning

confidence: 99%

Gaze and head pointing for hands-free text entry

Gizatdinova

Špakov

Tuisku

et al. 2018

Proceedings of the 2018 ACM Symposium on Eye Tracking Research &Amp; Applications

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With the proliferation 1 of small-screen computing devices, there has been a continuous trend in reducing the size of interface elements. In virtual keyboards, this allows for more characters in a layout and additional function widgets. However, vision-based interfaces (VBIs) have only been investigated with large (e.g., full-screen) keyboards. To understand how key size reduction affects the accuracy and speed performance of text entry VBIs, we evaluated gaze-controlled VBI (g-VBI) and head-controlled VBI (h-VBI) with unconventionally small (0.4°, 0.6°, 0.8° and 1°) keys. Novices (N = 26) yielded significantly more accurate and fast text production with h-VBI than with g-VBI, while the performance of experts (N = 12) for both VBIs was nearly equal whe n a 0.8-1° key size was used. We discuss advantages and limitations of the VBIs for typing with ultra-small keyboards and emphasize relevant factors for designing such systems. Figure 2: Columns show error rates (bars define 1 SEM from the means) of eye typing and face typing for novices (left) and experts (right). Scatter plots (red circles) account for error rates of individual typists. Key size Key size Figure 4: Columns show deletions, insertions and substitutions of eye typing (left bar for each key size) and face typing (right bar for each key size) for novices (left graph) and experts (right graph). Key size Key sizeFigure 3: Columns show KSPC (bars define 1 SEM from the means) of eye typing and face typing for novices (left) and experts (right). Scatter plots (red circles) account for KSPC values of individual typists.

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Life in the Fast Lane: Effect of Language and Calibration Accuracy on the Speed of Text Entry by Gaze

Cited by 10 publications

References 15 publications

EyeSwipe

EyeSwipe

Towards Pupil-Assisted Target Selection in Natural Settings: Introducing an On-Screen Keyboard

Gaze and head pointing for hands-free text entry

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