Evaluation of the Respective Effects of Microphone Type and Dummy Head Type on Measured Head-Related Transfer Functions
Bibliographic record
Abstract
A dummy head is a tool used to generate binaural recordings, i.e. recordings when listened to through headphones that allow for the listener to hear from the dummy's perspective. A dummy head typically includes pinnae and ear canals in which microphones are placed. The global shape of a dummy head replicates an average-sized human head, and variations around this average will depend on the manufacturer (pinnae of different size, presence of a nose or a mouth). This paper describes measurements conducted on two dummy heads in order to evaluate and rank the respective influence of microphone type and dummy head shape on spatialization cues. Four possible cross configurations are tested, that is head 1 or 2 with microphones pair 1 or 2. For each configuration, head-related transfer functions are measured in an anechoic room for various azimuth and elevation angles. The results obtained show that the effect of the dummy head shape is larger than the effect of the microphone type on measured head-related transfer functions. A practical implication of this result is found when microphones have to be replaced on a given dummy head.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".