Music and facial emotion recognition and its relationship with alexithymia
Bibliographic record
Abstract
The objective of this study was to determine the influence of alexithymia on the ability to identify emotions through visual and auditory stimuli. We assessed Alexithymia using the Toronto Alexithymia Scale (TAS-20). As visual stimuli, we employed the images of faces from the Ekman 60 Faces Test, while the auditory stimuli consisted of fragments of instrumental music. A total of 303 students participated, 139 in secondary education and 164 in the first year of university ( M = 17.58 years; SD = 4.16). The results show higher alexithymia levels in the female participants than in the male participants, mainly in the difficulty identifying feelings (DIF) and difficulty describing feelings (DDF) factors, and higher in the secondary students than in the university students, especially in externally oriented thinking (EOT). In terms of the identification of emotions through auditory stimuli, the EOT factor showed a strong predictive effect for the emotions of surprise and anger. For the visual stimuli, the EOT factor showed predictive validity for identifying happiness, while the DDF factor showed predictive validity for identifying sadness. We conclude that there is a relationship between alexithymia levels and emotion recognition, which varies depending on the nature of the stimulus.
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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 | 0.000 | 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) | 0.001 | 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".