Part Ia: Spatial separation on McGurk effect applying three-dimensional sounds
Bibliographic record
Abstract
The dependence of sound direction on the McGurk effect [McGurk and McDonald, Nature (London) 264, 746–748 (1976)] is less known. Jones and Munhall [Canadian Acoust. 25, 13–19 (1997)] concluded with no spatial separation dependence, applying 30° horizontally spaced loudspeakers. Current dual study investigated the full 360° horizontal space applying head-related transfer functions (HRTFs) from a Cortex dummy head [Riederer, J. Audio Eng. Soc. (Abstracts) 46, 1036 (1998), preprint 4846]. Dry acoustic /ipi/ and /iti/ recorded from a professional speaker were convolved with HRTFs, measured at azimuths 0°, ±40°, ±90°, ±130°, and 180°, headphones (Sennheiser HD580) equalized. DVcam-recorded visual /ipi/, /iti/ (and black screen) were randomly presented synchronously with the 3-D sounds using Presentation 0.20 [http://nbs.neuro-bs.com]. Totally 1024 incongruent audiovisual stimuli were perceived by eight 20–30-year-old normal hearing (≤20 dBHL) native subjects (2 female) as follows. Visual /ipi/ + auditory /iti/: /ipi/ 59.96%, /iti/ 15.63%, and /ipti/ 24.02%; visual /iti/ + auditory /ipi/: 66.02%, 22.07%, and 11.52%, respectfully. No significant dependence of spatial separation was found for the McGurk effect, except for reaction times. The obtained fusions were atypically weak, probably because visual /iti/ was less pronounced than visual /ipi/. [Work supported by Graduate School of Electronics, Telecommunication and Automation.]
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".