Where did that sound come from? Comparing the ability to localise using audification and audition
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.
Bibliographic record
Abstract
Purpose: A prototype device was developed to allow individuals to hear ultrasound reflections off environmental obstacles. Previous studies have shown that this device allows for better distance judgement than audition and allows for effective passage through the centreline of apertures. The purpose of this research was to evaluate audification as a method to localise direct sound sources as compared to audition. Method: In an anechoic environment, participants localised point-sound sources for three conditions: auditory, audified ultrasound with receivers facing laterally, and audified ultrasound with receivers facing forward. Results: Azimuth localisation was similar within a range of −35° to 35° in front of the participant among all conditions. At the periphery, −70° and 70°, audified ultrasound was more accurate than audition for novice participants. No difference was evident in user elevation accuracy for these signals among the different conditions. Conclusion: Audification of ultrasound can be effective for localising point-source sounds in the azimuth direction, but more evidence is required to evaluate accuracy in the vertical direction.Implications for RehabilitationSecondary mobility devices can be used by individuals with visual impairment to avoid obstacles above waist height.Audification allows for skill-based response enabling intuitive obstacle avoidance and localization of point sound sources.Localization of peripheral sounds was shown in this study to be better with audified ultrasound than audition.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it