Acting in action: Prosodic analysis of character portrayal during acting.
Bibliographic record
Abstract
During the process of acting, actors have to embody the characters that they are portraying by changing their vocal and gestural features to match standard conceptions of the characters. In this experimental study of acting, we had professional actors portray a series of stock characters (e.g., king, bully, lover), which were organized according to a predictive scheme based on the 2 orthogonal personality dimensions of assertiveness and cooperativeness. We measured 12 prosodic features of the actors' vocal productions, as related to pitch, loudness, timbre, and duration/timing. The results showed a significant effect of character assertiveness on all 12 vocal parameters, but a weaker effect of cooperativeness on fewer vocal parameters. These findings comprise the first experimental analysis of vocal gesturing during character portrayal in actors and demonstrate that actors reliably manipulate prosodic cues in a contrastive manner to differentiate characters based on their personality traits. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".