Reading aloud: Acoustic differences between prose and poetry
Bibliographic record
Abstract
Research on silent reading has shown that text genre influences the way texts are read, including differences between prose and poetry (e.g., Zwaan, 1994; Hanauer, 1998). There is little data examining whether text layout (prose vs. poetry) affects the way it is read aloud by non-expert readers, and, if yes, how do readers express those differences acoustically. Native speakers of Serbian (N = 28) and English (N = 37) read aloud twenty short texts in their native language. Stimuli were original texts that were acceptable as both prose and poetry, written by young published authors. Each text was formatted in four layouts (prose left aligned and justified, a single stanza and verses in multiple stanzas). Each participant saw each text in only one of these layouts. Separate mixed effects logistic regression analyses were performed for each language, testing whether prose vs. poetry layouts influenced the silent period and utterance duration, pitch, and intensity values of the productions. Differences and similarities between reading prose and poetry and between Serbian and English participants are discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 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".