Effects of Acoustic Speech Variation on Personality Trait Perception
Bibliographic record
Abstract
This thesis examines acoustic properties of speech which influence perceptions of personality traits, specifically charisma. The following questions are addressed: How does amplitude variation influence ratings of dominance (i), how does voice quality affect personality trait attribution (ii), and how does allophonic variation affect ratings of charisma (iii). Chapter 2 addresses question (i), finding that certain linguistic levels (increased amplitude in sentence and syllable levels) affected dominance ratings while others (increased amplitude at word level and reduction at syllable level) did not. Increased sentence amplitude increased dominance ratings while increased syllable amplitudes had inverse effects. Additionally, two types of dominance were examined (social and physical dominance) but no statistically significant differences were found between the two. Chapter 3 examines question (ii). All voice qualities investigated (modal, creaky, breathy, nasal, and smiling) were found to be statistically significant. Effect sizes for statistical significance varied for each voice quality. Creaky voice (rated the lowest/ most negative) and smiling voice (rated the highest/most positive) had the strongest effects. Chapter 4 examines question (iii). Experiment 1 (in-person) and Experiment 2 (online) examined the effects of allophonic variation, final consonant devoicing (FCD), and /t/ variation, on ratings of charisma. Experiment 1 found statistically significant rating differences for FCD. Final voiced items were rated higher compared to devoiced ones. For the /t/ variation, only speaker differences were found to be statistically significant. Experiment 2 showed no statistically significant results for FCD, whereas /t/ variation found statistical significance for [t] productions versus the glottal stop, and for flap productions versus the glottal stop. No rating differences were found between [t] and flap. Overall, this thesis demonstrates that some acoustic variations within speech affect personality trait ratings, specifically charisma, while others do not. I discuss reasons for these outcomes and their utilization in various domains, including AI.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".