The effect of native language and bilingualism on multimodal perception in speech: A study of audio-aerotactile integration
Bibliographic record
Abstract
Previous studies of speech perception revealed that tactile sensation can be integrated into the perception of stop consonants. It remains uncertain whether such multisensory integration can be shaped by linguistic experience, such as the listener's native language(s). This study investigates audio-aerotactile integration in phoneme perception for English and French monolinguals as well as English-French bilingual listeners. Six step voice onset time continua of alveolar (/da/-/ta/) and labial (/ba/-/pa/) stops constructed from both English and French end points were presented to listeners who performed a forced-choice identification task. Air puffs were synchronized to syllable onset and randomly applied to the back of the hand. Results show that stimuli with an air puff elicited more "voiceless" responses for the /da/-/ta/ continuum by both English and French listeners. This suggests that audio-aerotactile integration can occur even though the French listeners did not have an aspiration/non-aspiration contrast in their native language. Furthermore, bilingual speakers showed larger air puff effects compared to monolinguals in both languages, perhaps due to bilinguals' heightened receptiveness to multimodal information in speech.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".