Bibliographic record
Abstract
The voice onset time (VOT), which indicates the durational interval from the stop release to the start of the voicing of the following vowel, has long been a prominent research topic in the field of acoustic phonetics. It has shown to be a reliable universal acoustic parameter in discriminating the stop consonants in numerous languages, like English, German, Korean, and various Arabic varieties. It also has been claimed that other factors, such as place of articulation, gender, and vocalic contexts, may affect the productions of the VOTs of the stop categories. Therefore, the present study aims to examine the VOT values of the Najdi Arabic (NA) stops, particularly the plain stop consonants /b, d, g, t, k/, and the potential effects of the place of articulation, gender, and vocalic contexts on their production. Sixty male and female native NA speakers were recruited in this study. The findings revealed that NA has two types of VOTs: positive VOTs with the voiceless stops and negative VOTs with the voiced stops. They also showed that the VOTs of the NA stops become longer when the articulators move back to the oral cavity and shorter in the front cavity. Lastly, the findings reported that the VOTs with short vowels are significantly shorter than the VOTs with long vowels and that gender does not affect the VOTs of the voiced stops, but does affect the VOTs of their voiceless counterparts. Hopefully, the conclusions reached in this study contribute to a better understanding of this interesting acoustic parameter and to the less acoustic literature on Arabic and its various varieties.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".