Haptic-auditory interference from air flow in speech perception
Bibliographic record
Abstract
Previous work on haptic interference in auditory perception has shown McGurk-like effects from manual-tactile contact with the face [Fowler and Dekle, JEP:HPP 17, 816–828 (1991)]. The present study investigates whether indirect haptic input affects auditory perception. A novel method was developed in which one experimenter blew puffs of air onto a subject’s neck while another produced English plosives, creating possible mismatches between the sensation of aspiration and its acoustic presence. Subjects were blindfolded and wore headphones playing white noise. For 50% of the trial, one experimenter, whose presence was hidden from the subjects, blew puffs of air on subjects’ necks lightly enough to be perceived but not noticeable as unnatural. Simultaneously, a second experimenter produced syllables with bilabial plosive onsets (aspirated /p/ or unaspirated /b/) and subjects were asked to repeat what was heard. Sessions were videotaped and three observers rated successful simultaneity of stimuli. Results indicate cross-modal interference. Subjects showed higher accuracy of speech perception when appropriate haptic stimuli accompanied the auditory stimuli. Moreover, when presented with mismatched tactile and auditory stimuli, subjects demonstrated the fusion of the two modes. Subjects perceived /pa/ when auditory stimulus /ba/ was presented with emulating aspiration. [Work supported by NSERC.]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".