The effects of incidental learning and input frequency on the perception of non-native speech
Bibliographic record
Abstract
The current study investigated the extent to which naive listeners could incidentally acquire non-native phonemic contrasts and the degree to which the frequency of exposure to the target phonemes affects their learning. A total of 100 English speakers were assigned to the following conditions: (1) 0-occurrence; (2) 2-occurrence; (3) 10-occurrence; (4) 20-occurrence; or (5) 30-occurrence. The participants watched a video that provided instruction on counting numbers in Korean while incidentally exposing them to various repetitions of the target phonemes. All participants completed a pretest, an immediate posttest, and a delayed posttest, each comprising an AX discrimination task. The effects of incidental exposure were found only in the 10-occurrence condition, in both the immediate posttest and the delayed posttest. While the current study demonstrates the overall efficacy of incidental exposure on the perception of non-native speech, it also highlights the important role that selective attention plays in language learning.
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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 | 0.002 | 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 | 0.000 | 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) | 0.024 | 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".