Learning a Phonological Contrast Modulates the Auditory Grouping of Rhythm
Bibliographic record
Abstract
Perceptual grouping is fundamental to many auditory processes. The Iambic-Trochaic Law (ITL) is a default grouping strategy, where rhythmic alternations of duration are perceived iambically (weak-strong), while alternations of intensity are perceived trochaically (strong-weak). Some argue that the ITL is experience dependent. For instance, French speakers follow the ITL, but not as consistently as German speakers. We hypothesized that learning about prosodic patterns, like word stress, modulates this rhythmic grouping. We tested this idea by training French adults on a German-like stress contrast. Individuals who showed better phonological learning had more ITL-like grouping, particularly over duration cues. In a non-phonological condition, French adults were trained using identical stimuli, but they learned to attend to acoustic variation that was not linguistic. Here, no learning effects were observed. Results thus suggest that phonological learning can modulate low-level auditory grouping phenomena, but it is constrained by the ability of individuals to learn from short-term training.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".