Multimodal Interaction of Contextual and Non-Contextual Sound and Haptics in Virtual Simulations
Bibliographic record
Abstract
Touch plays a fundamental role in our daily interactions, allowing us to interact with and perceive objects and their spatial properties. Despite its importance in the real-world, touch is often ignored in virtual environments. However, accurately simulating the sense of touch is difficult, requiring the use of high-fidelity haptic devices that are cost-prohibitive. Lower fidelity consumer-level haptic devices are becoming more widespread, yet are generally limited in perceived fidelity and the range of motion (degrees of freedom) required to realistically simulate many tasks. Studies into sound and vision suggest that the presence or absence of sound can influence task performance. Here, we explore whether the presence or absence of contextually relevant sound cues influences the performance of a simple haptic drilling task. Although the results of this study do not show any statistically significant difference in task performance with general (task-irrelevant) sound, we discuss how this is a necessary step in understanding the role of sound on haptic perception.
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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 | 0.000 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".