The Impressionistic Study of English /tʃ/ and /ʃ/ in Initial Position by L2 Thai Learners
Bibliographic record
Abstract
Although studies on English sound learning by L2 Thai learners have been widely examined, there have been no studies on the production of the English /tʃ/ and /ʃ/ sounds in the initial position by L2 Thai learners with consideration of vowel contexts, the experience of L2 learners and target sounds. The aim of this study is to examine the production of the English /tʃ/ and /ʃ/ sounds in the initial position while taking the aforementioned factors into account. The data was from 48 L2 Thai learners, and the subjects were divided into two groups of university students: English-majors and non-English-majors. The two target sounds: English /tʃ/ and /ʃ/ together with the Thai /tɕʰ/ sound were tested in 27 words (9 words for each target sound). The subjects produced the target sounds five times, and their production was transcribed by two British transcribers. The results showed that the subjects had high target-like production when producing /ʃ/ but low target-like production when producing /tʃ/. In finding the correlation between the factors and the target-like production, neither the vowel contexts nor the experience could account for the production. The only factor that relates to the production of English /tʃ/ and /ʃ/ was the target sounds, i.e. the number of the productions that was deemed non-target-like was significantly higher when the target sound was /tʃ/ than when it was /ʃ/. This suggests that the target sounds, rather than the L2 experience and the vowel contexts, play a significant role in L2 speech production.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".