Perception of English /r/ and /l/ speech contrasts by native Korean listeners with extensive English-language experience
Bibliographic record
Abstract
Native speakers of Korean often have difficulty perceiving the English /r/-/l/ sounds. In view of this, we sought to examine the degree to which very extensive exposure to the English language as an adult, through many years of living in a predominantly English-language environment, affects the perception of "difficult" English speech contrasts such as /r/-/l/. This study was therefore designed to study aspects of the speech perception abilities of adults who were native speakers of Korean but who had lived for many years in an English-speaking environment. The ability to distinguish English /r/ vs. /l/ contrasts was measured using a two-alternative forced-choice [r-l] identification task. 12-bit, 10-kHz sampled signals were processed digitally to convert them to the format required for our computer programs. The resulting signals were stored on computer disk as 16-bit, 16-kHz signals in CSRE (Canadian Speech Research Environment) format. This [r-l] test consisted of five minimal pairs (e.g. rock-lock) within each of five phonetic environments: initial singleton, initial consonant cluster, medial, final consonant cluster, and final singleton.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".