Lexical encoding of second language tones in English learners of Mandarin
Bibliographic record
Abstract
The study investigates how native and non-native differences in tone perception influence lexical encoding of second language (L2) tones. Previous work shows that tone language listeners perceived tones as phonemic categories while non-tone language listeners relied more on psychoacoustic cues such as pitch height to discriminate stimulus tones. However, little is known about the influence of such differences in perception on L2 tonal encoding. In the present study, two experiments were conducted with nineteen English learners of Mandarin and 20 Mandarin native speakers. Experiment 1 was an ABX task. Results showed that while native speakers’ overall performance was superior to L2 listeners’, both groups poorly discriminated tone pairs with shared tone contours (i.e., T2-T3). Experiment 2 was a medium-lag repetition priming task. In the repetition condition, significant facilitations were observed in both language groups. In the minimal-tone-pair condition, despite T2-T3 contrasts posing greater challenge for both groups to accurately distinguish than other tonal contrasts as shown in Experiment 1, positive priming was observed only in the L2 group. The findings from the two experiments suggest that the L2 listeners, although quite proficient in Mandarin, have yet to achieve native-like competence in regard to lexical tones.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".