Effects of Different Auditory Feedback Frequencies in Virtual Reality 3D Pointing Tasks
Bibliographic record
Abstract
Auditory error feedback is commonly used in 3D Virtual Reality (VR) pointing experiments to increase participants' awareness of their misses. However, few papers describe the parameters of the auditory feedback, such as the frequency. In this study, we asked 15 participants to perform an ISO 9241-411 pointing task in a distributed remote experiment. In our study, we used three forms of auditory feedback, i.e., C4 (262 Hz), C8 (4186 Hz) and none. According to the results, we observed a speed-accuracy trade-off for the C8 tones compared to C4 ones: subjects were slower, and their throughput performance decreased with the C8 while their error rate decreased. Still, for larger targets there was no speed-accuracy trade-off, and subjects were only slower with C8 tones. Overall, the frequency of the feedback had a significant impact on the user's performance. We thus suggest that practitioners, developers, and designers report the frequency they used in their VR applications.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".