Designing, Implementing and Evaluating a Cross-Modal Sensory Substitution System for the Effective Communication of the Emotional and Informative Aspects of Music
Bibliographic record
Abstract
Visualizations have existed for millennia as ways to communicate information. Visualizations are ubiquitous tools used every day to help navigate cities and aid in learning complex tasks. Tasks are made simpler when applying various visualization methods to large data sets to discover trends that are otherwise difficult to notice. More recently, music visualization systems have been created to convey music in the visual domain; however, they are not based on any psychological model of auditory and visual equivalents. This thesis discusses a music visualization system called MusicViz, which facilitates in the visual communication of the informative and entertainment aspect of music based on psychologically justified translation principals. MusicViz is combined with a vibro-feedback chair called the Emoti-Chair, which translates auditory music to vibrations along the user’s back. The combined system is coined VITA (Visually Immersive and Tactile Animation). A usability evaluation of the VITA showed it is an enjoyable experience.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".