The perceptual normalization of lexical tones: effects of surrounding tonal context
Bibliographic record
Abstract
Previous research has shown that the perceptual categorization of a target lexical tone depends on its surrounding tonal context (“tone normalization”). Native speakers have been shown to take into account both preceding and following tonal context in order to carry out the normalization process. The present study focused on the effects of the duration and type of preceding tonal context on tone normalization. Listeners identified the tone of a syllable in final sentence position, as a function of the number of syllables (1, 2, 3, or 4) and of the tone type (level or contour) of a semantically-neutral precursor sentence. The results showed that: 1. The effect of the precursor sentence reached an asymptote once listeners heard two syllables; 2. The tone type of the precursor sentence did not affect performance. This evidence is consistent with a tone normalization process that operates on the basis of a running F0 average of the surrounding tonal context. When tonal context precedes the target tone, the running F0 average is effectively computed over a two-syllable interval.
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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 | 0.009 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".