A note on the acoustic-phonetic characteristics of non-native English vowels produced in noise
Bibliographic record
Abstract
The Lombard reflex occurs when people unconsciously raise their vocal levels in the presence of loud background noise. Previous work has established that utterances produced in noisy environments exhibit increases in vowel duration and fundamental frequency (F0), and a shift in formant center frequencies for F1 and F2. Most studies of the Lombard reflex have been conducted with native speakers; research with second-language speakers is much less common. The present study examined the effects of the Lombard reflex on foreign-accented English vowel productions. Seven female Cantonese speakers and a comparison group of English speakers were recorded producing three vowels (/i u a/) in /bVt/ context in quiet and in 70 dB of masking noise. Vowel durations, F0, and the first two formants for each of the three vowels were measured. Analyses revealed that vowel durations and F0 were greater in the vowels produced in noise than those produced in quiet in most cases. First formants, but not F2, were consistently higher in Lombard speech than in normal speech. The findings suggest that non-native English speakers exhibit acoustic-phonetic patterns similar to those of native speakers when producing English vowels in noisy conditions.
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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 | 0.000 | 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".