Discrimination of Second Language Vowel Contrasts and the Role of Phonological Short-Term Memory and Nonverbal Intelligence
Why this work is in the frame
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Bibliographic record
Abstract
Although extensive research has focused on the perceptual abilities of second language (L2) learners, a significant gap persists in understanding how cognitive functions like phonological short-term memory (PSTM) and nonverbal intelligence (IQ) impact L2 speech perception. This study sets out to investigate the discrimination of L2 English monophthongal vowel contrasts and to assess the effect of PSTM and nonverbal IQ on L2 speech perception. The participants consisted of adult monolingually-raised Greek speakers, who completed an AX discrimination test, a digit span test, and a nonverbal intelligence test. A control group of English speakers also completed the AX test. Data were analyzed using Bayesian regression models. The results revealed that Greek speakers exhibited below chance discrimination for the majority of L2 vowel contrasts, consistently underperforming in comparison to the control group. Intriguingly, the study did not provide substantial evidence in favor of more accurate discrimination of L2 contrasts by Greek participants with high PSTM compared to those with low PSTM. However, the study yielded compelling evidence indicating that Greek participants with higher IQ demonstrated superior accuracy in discriminating most L2 contrasts compared to their lower IQ counterparts. The limited influence of PSTM on speech perception suggests the need for further exploration, considering the potential impact of test methodologies and the intricate interplay of other confounding factors. Furthermore, the study uncovers a noteworthy relationship between nonverbal IQ and L2 speech perception, likely linked with the association of high IQ with enhanced attentional capacities, information processing abilities, and learning skills-all of which are pivotal for accurate speech perception.
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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 | 0.004 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it