Testing symmetry of temporal window of integration between vibrotactile and auditory speech information in voiced phoneme perception
Bibliographic record
Abstract
The temporal window for enhancement in cross-modal integration is asymmetrical, and does not require synchrony of stimuli for integration; this temporal offset has been linked to differences in relative signal speed as can be seen in audio-visual integration [Munhall et al. 1996. Perc. Psychophys. 58: 351] and audio-aerotactile integration [Gick et al. 2010. Journ. Acoust. Soc. Am. 128: EL342] of speech. However, as vibrotactile cues normally accompany acoustic cues, no difference in signal speed—and no concomitant perceptual asymmetry—is experienced between these two modalities. Contrary to previous research, we predict a symmetrical window for integration. A portable voice-coil transducer is used to produce vibrotactile stimuli, similar to the laryngeal vibrations normally felt in voiced speech. Results of an experiment will be presented in which participants are asked to discriminate between minimal pairs in noise with the device between their thumb and index finger, and in which audio and vibrotactile stimuli are presented in different orders and at different temporal offsets. Implications will be discussed for theories of cross-modal integration. [Funding from NSERC.]
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.007 | 0.001 |
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".