Characterizing Speech Sound Productions in Bilingual Speakers of Jamaican Creole and English: Application of Durational Acoustic Methods
Bibliographic record
Abstract
PURPOSE: This study examined the speech acoustic characteristics of Jamaican Creole (JC) and English in bilingual preschoolers and adults using acoustic duration measures. The aims were to determine if, for JC and English, (a) child and adult acoustic duration characteristics differ, (b) differences occur in preschoolers' duration patterns based on the language spoken, and (c) relationships exist between the preschoolers' personal contextual factors (i.e., age, sex, and percentage of language [%language] exposure and use) and acoustic duration. METHOD: = 15, ages 19;0-54;4) from the same linguistic community. Audio recordings of single-word productions of JC and English were collected through elicited picture-based tasks and used for acoustic analysis. Durational features (voice onset time [VOT], vowel duration, whole-word duration, and the proportion of vowel to whole-word duration) were measured using Praat, a speech analysis software program. RESULTS: JC-English-speaking children demonstrated developing speech motor control through differences in durational patterns compared with adults, including VOT for voiced plosives. Children's VOT, vowel duration, and whole-word duration were produced similarly across JC and English. The contextual factor %language use was predictive of vowel and whole-word duration in English. CONCLUSIONS: The findings from this study contribute to a foundation of understanding typical bilingual speech characteristics and motor development as well as schema in JC-English speakers. In particular, minimal acoustic duration differences were observed across the post-Creole continuum, a feature that may be attributed to the JC-English bilingual environment. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.21760469.
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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 | 0.001 |
| 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".