Is there an interlanguage intelligibility benefit in perception of English word stress?
Bibliographic record
Abstract
This paper asks whether there is an ‘interlanguage intelligibility benefit’ in perception of word-stress, as has been reported for global sentence recognition. L1 English listeners, and L2 English listeners who are L1 speakers of Arabic dialects from Jordan and Egypt, performed a binary forced-choice identification task on English near-minimal pairs (such as[ˈɒbdʒɛkt] ~ [əbˈdʒɛkt]) produced by an L1 English speaker, and two L2 English speakers from Jordan and Egypt respectively. The results show an overall advantage for L1 English listeners, which replicates the findings of an earlier study for general sentence recognition, and which is also consistent with earlier findings that L1 listeners rely more on structural knowledge than on acoustic cues in stress perception. Non-target-like L2 productions of words with final stress (which are primarily cued in L1 production by vowel reduction in the initial unstressed syllable) were less accurately recognized by L1 English listeners than by L2 listeners, but there was no evidence of a generalized advantage for L2 listeners in response to other L2 stimuli.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".