Prosodic realization and interpretation of English imperatives
Bibliographic record
Abstract
Imperative clauses can communicate a number of speech acts, and differences in intonation have been argued to prompt different interpretations. So far, however, limited phonetic evidence has been presented for such proposals. The focus in the current work is on maximally strong imperatives (commands) and weaker imperatives (mainly involving advice) in English. We report on a series of phonetic experiments intended to address whether listeners reliably associate stronger and weaker imperatives with idealized intonation (Experiment 1) and whether speakers produce these two types of imperatives differently (Experiment 2). Individual variability in our production data led us to test whether listeners can map the variable pronunciation patterns found in Experiment 2 to stronger and weaker imperatives (Experiment 3), as they did with the idealized pronunciations in Experiment 1. Despite substantial cross-talker intonation variation, listeners’ stronger/weaker imperative recognition performance paralleled accuracy with the idealized productions. Analysis of the whole utterances indicates that speech rate and global pitch setting work along with the final intonation contour to signal semantic meaning in English imperatives. These results suggest that the mapping between meaning and form is complex and involves redundancy.
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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 | 0.000 | 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 | 0.000 |
| 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 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".