Between /u/ and /y/: Vowel merger perception in heritage Cantonese
Bibliographic record
Abstract
Vowels are particularly subject to change in the language contact situation of Cantonese in North America. For example, Author 4 (2024a, 2024b) shows acoustic evidence of the merger of /y/ and /u/. This may be due to influence from English, which lacks a similar vowel contrast. This merger was found only among Toronto speakers and is completely absent in Hong Kong Cantonese. Up to this point, research on this merger has been limited to production-based studies. In this study, we address the perceptual merger of /u/ and /y/ and how it may be influenced by Cantonese language proficiency. Heritage speakers of Cantonese in Hawaiʻi (N = 30) were tested using an AB discrimination task to test whether they have the merger in perception, using syllables produced by an L1 Cantonese speaker as stimuli. Accuracy and reaction times from the task were analyzed as a function of Cantonese proficiency to determine the progress of the merger. Cantonese proficiency was also determined by both prompted speaking assessment tasks and self-assessment through a language background survey. Data collection is ongoing; preliminary analysis of a pilot shows evidence of an incomplete merger: Heritage listeners are still able to distinguish /u/ and /y/ with high accuracy.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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 | 0.000 |
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".