Intelligibility, Comprehensibility, and Accentedness of L2 Speech: The Role of Listener Experience and Semantic Context
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract: This study investigated how listener experience (extent of previous exposure to non-native speech) and semantic context (degree and type of semantic information available) influence measures of intelligibility, comprehensibility, and accentedness of non-native (L2) speech. Participants were 24 native English-speaking listeners, half experienced and half inexperienced with L2 speech, who transcribed and rated 90 English utterances spoken by six English and six Mandarin speakers. The utterances varied along two dimensions: real-world expectations (true vs. false utterances) and semantic meaningfulness (meaningful vs. meaningless utterances). Listeners with more experience understood more speech from the L1 and L2 speakers than listeners with less experience but did not rate it differently in comprehensibility and accentedness. All listeners understood and rated the utterances from L2 speakers based on the semantic context available: true–false utterances were understood and rated best, meaningless utterances least. These findings have implications for evaluating learner pronunciation and for training learners in successful L2 communication strategies.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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