Bibliographic record
Abstract
Introduction Can nasal vowels, like oral vowels, devoice? While phonemic voiceless nasal consonants are found in a variety of languages, phonemic voiceless nasal vowels appear unattested (Ladefoged & Maddieson, 1996; Crothers et al., 1979). Typological evidence also suggests that phonological processes of vowel devoicing eschew nasal vowel targets. Of the 55 languages with voiceless vowels or vowel devoicing processes catalogued by Gordon (1998), only four of these also have phonemically nasal vowels. These are Bagirmi, Montreal French, Mbay, Mixtec, and Brazilian Portuguese. While it is clear that nasal vowel devoicing is impossible in French and Portuguese, a review of the other languages reveals no positive evidence that it is possible (or impossible) for nasal vowels to be realized without vocal fold vibration. This paper asks whether acoustic factors may present barriers to the perception of voiceless nasal vowels. A series of perceptual experiments using whispered nasal and oral vowels of Brazilian Portuguese will test whether “devoiced” nasal vowels are more difficult to identify than “devoiced” oral vowels. The acoustic characteristics of whispered nasal vowels will also be examined to see if they provide any clues as to the typological rarity of nasal vowel devoicing.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".