Aging Affects Identification of Vocal Emotions in Semantically Neutral Sentences
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The authors determined the accuracy of younger and older adults in identifying vocal emotions using the Toronto Emotional Speech Set (TESS; Dupuis & Pichora-Fuller, 2010a) and investigated the possible contributions of auditory acuity and suprathreshold processing to emotion identification accuracy. METHOD: In 2 experiments, younger and older adults with normal hearing listened to and identified vocal emotions in the TESS stimuli. The TESS consists of phrases with controlled syntactic, lexical, and phonological properties spoken by an older female talker and a younger female talker to convey 7 emotion conditions (anger, disgust, fear, sadness, neutral, happiness, and pleasant surprise). Participants in both experiments completed audiometric testing; participants in Experiment 2 also completed 3 tests of suprathreshold auditory processing. RESULTS: Identification by both age groups was above chance for all emotions. Accuracy was lower for older adults in both experiments. The pattern of results was similar across age groups and experiments. Auditory acuity did not predict identification accuracy for either age group in either experiment, nor did performance on tests of auditory processing in Experiment 2. CONCLUSIONS: These results replicate and extend previous findings concerning age-related differences in ability to identify vocal emotions and suggest that older adults' auditory abilities do not explain their difficulties in identifying vocal emotions.
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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 | 0.003 | 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 | 0.000 | 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 it