Voice Onset Time in English voiceless stops is affected by following postvocalic liquids and voiceless onsets
Bibliographic record
Abstract
Voice Onset Time is an important characteristic of stop consonants that plays a large role in perceptual discrimination in many languages, and is widely used in phonetic research. The current paper aims to account for Voice Onset Time variation in English that has defied previously understood phonetic and lexical factors, particularly involving stops that are followed in the word by liquids and voiceless obstruents. 122 Canadian English speakers produced 120 /p/- and /k/-initial words (n = 17 533), and word-initial Voice Onset Time was analyzed. It was found that Voice Onset Time is shorter when the following syllable starts with a voiceless obstruent, and that this effect is mediated by speech rate. Voice Onset Time is also longer before postvocalic liquids, even when they are intervocalic. Voice Onset Time generally decreases through the course of the task, and speakers tend to drift during the course of a word reading task, and this is best accounted for by the residual Voice Onset Time of recently spoken words.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".