Effects of Word Position on the Acoustic Realization of Vietnamese Final Consonants
Bibliographic record
Abstract
A variety of studies have shown differences between phonetic features of consonants according to their prosodic and/or syllable (onset vs. coda) positions. However, differences are not always found, and interactions between the various factors involved are complex and not well understood. Our study compares acoustical characteristics of coda consonants in Vietnamese taking into account their position within words. Traditionally described as monosyllabic, Vietnamese is partially polysyllabic at the lexical level. In this language, tautosyllabic consonant sequences are prohibited, and adjacent consonants are only found at syllable boundaries either within polysyllabic words (CVC.CVC) or across monosyllabic words (CVC#CVC). This study is designed to examine whether or not syllable boundary types (interword vs. intraword) have an effect on the acoustic realization of codas. The results show significant acoustic differences in consonant realizations according to syllable boundary type, suggesting different coarticulation patterns between nuclei and codas. In addition, as Vietnamese voiceless stops are generally unreleased in coda position, with no burst to carry consonantal information, our results show that a vowel's second half contains acoustic cues which are available to aid in the discrimination of place of articulation of the vowel's following consonant.
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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) | 0.004 | 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".