Sound localization with communications headsets: Comparison of passive and active systems
Bibliographic record
Abstract
Studies have demonstrated that conventional hearing protectors interfere with sound localization. This research examines possible benefits from advanced communications devices. Horizontal plane sound localization was compared in normal-hearing males with the ears unoccluded and fitted with Peltor H10A passive attenuation earmuffs, Racal Slimgard II communications muffs in active noise reduction (ANR) and talk-through-circuitry (TTC) modes and Nacre QUIETPRO TM communications earplugs in off (passive attenuation) and push-to-talk (PTT) modes. Localization was assessed using an array of eight loudspeakers, two in each spatial quadrant. The stimulus was 75 dB SPL, 300-ms broadband noise. One block of 120 forced-choice loudspeaker identification trials was presented in each condition. Subjects responded using a laptop response box with a set of eight microswitches in the same configuration as the speaker array. A repeated measures ANOVA was applied to the dataset. The results reveal that the overall percent correct response was highest in the unoccluded condition (94%). A significant reduction of 24% was observed for the communications devices in TTC and PTT modes and a reduction of 49% for the passive muff and plug and muff with ANR. Disruption in performance was due to an increase in front-back reversal errors for mirror image spatial positions. The results support the conclusion that communications devices with advanced technologies are less detrimental to directional hearing than conventional, passive, limited amplification and ANR devices.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".