Vowel-inherent spectral change in isolated vowels and consonant vowel consonants.
Bibliographic record
Abstract
To study the interaction of vowel inherent spectral change (VISC) and consonant context on vowel formant patterns, we recorded 15 vowels /i ɪ eɪ ε æ ʌ ɑ ɔ oU U u ɝ ɑɪ ɑU ɔɪ/ in each of 14 consonant environments (pVp, pVb, bVb, bVp, tVt, tVd, dVt, dVd, kVk, kVg, gVk, gVg, hVd, and V) spoken by 10 men and 10 women from the north Texas region. Analysis of vowel formant frequency trajectories confirmed the reliable presence of VISC across talkers for a range of consonant environments. Vowels showing stable patterns of VISC included those acknowledged as diphthongs in most North American English dialects, /ɑɪ/, /ɑU/, /ɔɪ/, /eɪ/, /oU/, as well as /ɪ/, with more variable movement patterns for /ε/, /æ/, and /u/. Of particular interest were cases where the formants F1 and/or F2 showed a “switchback” pattern of movement, with initial movement in the expected direction for the vowel (as observed in isolated vowels) and subsequently toward the“locus” for the final consonant. Parallel analyses of VISC in three dialects (north Texas, Nova Scotia, and Alberta) are currently underway and will be reported at the meeting along with statistical modeling results [Nearey (this meeting)].
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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 | 0.000 | 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".