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Record W4235523709 · doi:10.32920/ryerson.14646297.v1

Designing and Evaluating an Interface for the Composition of Vibro-Tactile Patterns Using Gestures

2021· preprint· en· W4235523709 on OpenAlexaff
Sai Chaitanya Cherukumilli

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsGestureInterface (matter)Computer scienceUsabilityMotion (physics)Human–computer interactionVibrationGesture recognitionAcousticsArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Human-computer interaction systems have been providing new ways for amateurs to compose music using traditional computer peripherals as well as gesture interfaces. Vibro-tactile patterns, which are a vibrational art form similar to auditory music, can also be composed using human-computer interfaces. This thesis discusses the gesture interface system called the Vibro-Motion, which facilitates the composition of vibro-tactile patterns in real-time on an existing tactile sensory substitution system called the Emoti-Chair. The Vibro-Motion allows users to control the pitch, magnitude of the vibration as well as the position of the vibration. A usability evaluation of Vibro-Motion system showed it to be intuitive, comfortable and enjoyable for the participants.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.097
GPT teacher head0.363
Teacher spread0.266 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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