Age-related differences in the production and recognition of vocal socio-emotional expressions
Bibliographic record
Abstract
The present thesis examined age-related differences and individual factors associated with youth's and adults' ability to produce and recognize socio-emotional expressions in the voice.Vocal cues in a speaker's tone of voice are an important source of social information, yet they remain an understudied form of emotional communication.The studies presented herein examine both the encoding and decoding of affective prosody by youth and adults.Though previous work has typified the patterns of acoustic cues used by adults when portraying "basic" emotions, such as happiness and anger, virtually no data exists on the production of emotional prosody by youth.Study 1 compared the vocal cues underlying 24 young actors' portrayals of various expressions to those of 30 adult actors, to determine whether there were age-related differences in the ways in which both age groups conveyed basic emotions (anger, disgust, fear, happiness, sadness) and social expressions of meanness and friendliness.Findings suggest that youth and adults differ in their portrayals of vocal expressions in ways that are likely to be perceptually meaningful.Specifically, adults' vocal expressions were more distinct in pitch from one another than those of adolescents; given the influence of pitch cues on the identification of emotional intent in the voice (Pell et al., 2009;Scherer, 1996), the results of Study 1 suggest that adults' emotional prosody may be easier for listeners to decode than those of youth.Building on this result, Study 2 examined how speaker age, listener age, and the interaction between these two factors were each associated with listeners' vocal decoding skills.Fifty youth and 87 adult listeners were asked to identify the intended expression in recordings produced by youth and adult actors (from Study 1).Adult listeners were more accurate in recognition than were younger listeners, aligning with previous evidence that vocal decoding
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".