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Record W2544344441 · doi:10.1109/tic-sth.2009.5444381

Eyes-free text entry on a touchscreen phone

2009· article· en· W2544344441 on OpenAlex
Hussain Tinwala, I. Scott MacKenzie

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsYork University
Fundersnot available
KeywordsTouchscreenText entryMode (computer interface)Hands freeComputer scienceText messagingMobile devicePhoneSpeech recognitionHuman–computer interaction

Abstract

fetched live from OpenAlex

We present an eyes-free text entry technique for touchscreen mobile phones. Our method uses Graffiti strokes entered using a finger on a touchscreen. Although visual feedback is present, eyes-free entry is possible using auditory and tactile stimuli. In eyes-free mode, entry is guided by speech and non-speech sounds, and by vibrations. A study with 12 participants was conducted using an Apple iPhone. Entry speed, accuracy, and stroke formations were compared between eyes-free and eyes-on modes. Entry speeds reached 7.00 wpm in the eyes-on mode and 7.60 wpm in the eyes-free mode. Text was entered with an overall accuracy of 99.6%. KSPC was 9% higher in eyes-free mode, at 1.36, compared to 1.24 in eyes-on mode.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.248
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations39
Published2009
Admission routes1
Has abstractyes

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