Spoken word recognition in a second language: The importance of phonetic details
Why this work is in the frame
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Bibliographic record
Abstract
Spoken word recognition depends on variations in fine-grained phonetics as listeners decode speech. However, many models of second language (L2) speech perception focus on units such as isolated syllables, and not on words. In two eye-tracking experiments, we investigated how fine-grained phonetic details (i.e. duration of nasalization on contrastive and coarticulatory nasalized vowels in Canadian French) influenced spoken word recognition in an L2, as compared to a group of native (L1) listeners. Results from L2 listeners (English-native speakers) indicated that fine-grained phonetics impacted the recognition of words, i.e. they were able to use nasalization duration variability in a way similar to L1-French listeners, providing evidence that lexical representations can be highly specified in an L2. Specifically, L2 listeners were able to distinguish minimal word pairs (differentiated by the presence of phonological vowel nasalization in French) and were able to use variability in a way approximating L1-French listeners. Furthermore, the robustness of the French "nasal vowel" category in L2 listeners depended on age of exposure. Early bilinguals displayed greater sensitivity to some ambiguity in the stimuli than late bilinguals, suggesting that early bilinguals had greater sensitivity to small variations in the signal and thus better knowledge of the phonetic cue associated with phonological vowel nasalization in French, similarly to L1 listeners.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.113 | 0.001 |
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 it