VOT Analysis of L1 and L2 Speakers of Itza’
Bibliographic record
Abstract
This study explores Voice Onset Time (VOT) in Itza’, a critically endangered Mayan language. VOT is the amount of time elapsed between the release burst of a stop sound such as /p/ or /t/ and the onset of voicing associated with the following vowel; this measurement can vary for the same phoneme across languages and intra-language variation is also found. Research on other languages like SENĆOŦEN has reported that L2 teachers produced a ”stronger” ejective /t’/ than L1 elders, with a longer VOT (Bird 2020). Itza’ is in a similar situation as SENĆOŦEN, with ongoing language revitalization efforts focused on producing a new generation of L2 speakers; this motivated the present analysis of Itza’ ejectives to determine whether there are differences in VOT values of ejective stops and to discuss how this may impact language revitalization efforts. Elicitation sessions using a wordlist with 8 Itza’ speakers (L1 and L2) produced 216 tokens of ejective and plain stops followed by both /a/ and /u/. VOT was segmented and extracted using Praat (Boersma and Weenink 2022). A mixed-effects model was created using R (Bates et al. 2015) with L1/L2 status, airstream mechanism, place of articulation, and following vowel as fixed effects and Speaker ID as grouping variable. L1/L2 speaker status was found to have a significant effect on VOT at the p < 0.05 level, with L1 speakers having a higher VOT than L2s. This could indicate that ejectives in Itza’ are weakening over time, which may have long-term effects on the retention of these sounds in the language due to reduced salience (Ham 2008, 61–62). An effect of vowel at the p < 0.05 level was also found: stops followed by vowel /a/ had a higher VOT than those followed by vowel /u/. Bibliography Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1–48. Bird, S. (2020). Pronunciation among adult Indigenous language learners. Journal of Second Language Pronunciation, 6(2), 148–179. Boersma, P., & Weenink, D. (2022). Praat: Doing phonetics by computer (6.3.02). Ham, S. (2008). Tsilhqut’in Ejectives: A Descriptive Phonetic Study [Thesis]. University of Victoria.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".