Effects of noise on performance and perceived annoyance in Stroop tasks
Bibliographic record
Abstract
Psychoacoustic laboratory investigations of annoyance from prolonged exposure to environmental noise stimuli may require that subjects are engaged in a cognitive task while being exposed to the noise. This setup for collecting subjective annoyance represents a so-called unfocused listening experiment. Thereby, annoyance ratings would be collected after noise playback. Finding appropriate tasks, however, can be challenging. Firstly, doing a monotonous task for prolonged periods of time could be tiresome. Secondly, learning effects due to repetition(s) may bias the results. Hence, it is desirable to incorporate similar tasks of comparable difficulty, that can be used interchangeably, and the performance of which should not be affected by noise differently. The objective of the present study was to test whether different versions of the so-called Stroop task fulfill these requirements. In two pilot experiments, several variations of the Stroop task were tested regarding the two criteria of task similarity and comparable difficulty. Based on the results, two types of Stroop task were selected for the main experiment. Here, subjects were seated in a genuine office repurposed for this experiment, whilst performing the different versions of the Stroop task in three sound conditions: silence (<em>L</em><sub>Aeq</sub> = 26 dBA), low-level background sound of birds and vegetation (<em>L</em><sub>Aeq</sub> = 32 dBA), and road traffic noise superimposed on the mentioned background sound (<em>L</em><sub>Aeq</sub> = 45 dBA). Reaction times and error rates were measured. After the experiment, subjects were asked which sounds they found the least and the most annoying. Although no significant differences were found in Stroop task performance between the three sound conditions, annoyance judgements differed: road traffic noise was found to be more annoying than silence or background sound. We conclude that the chosen versions of the Stroop task are suitable for unfocused listening experiments on annoyance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".