A Comparison Between Active and Passive Approaches to the Sound Quality Tuning of a High Performance Vehicle
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">Sports car sound quality regularly has two conflicting targets, meeting customer's expectations for interior noise and enhancing the driving experience whilst complying with exterior noise legislation. To help with this balancing act acoustics engineers have an ever growing arsenal of tools to choose from. The conventional sound character development approach would typically involve the tuning of existing vehicle systems, primarily the air-intake and exhaust system. Increased flexibility to interior noise sound character tuning has been offered by the development of sound enhancement devices. The number of sound enhancement devices now commercially available has grown significantly in recent years but the systems can be broadly split into two main categories. Passive systems such as intake sound generators that aim to boost the levels of existing noise sources and more recently the advent of electronic sound enhancement through loud speakers and inertia shakers. This paper presents the results of a sound quality tuning exercise conducted on a Bentley Continental GT which compared differing approaches for three attributes; sound quality, ease of implementation and customer perception.</div></div>
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 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".