Recognizing vocal expressions of emotion in patients with social skills deficits following traumatic brain injury
Bibliographic record
Abstract
Perception of emotion in voice is impaired following traumatic brain injury (TBI). This study examined whether an inability to concurrently process semantic information (the "what") and emotional prosody (the "how") of spoken speech contributes to impaired recognition of emotional prosody and whether impairment is ameliorated when little or no semantic information is provided. Eighteen individuals with moderate-to-severe TBI showing social skills deficits during inpatient rehabilitation were compared with 18 demographically matched controls. Participants completed two discrimination tasks using spoken sentences that varied in the amount of semantic information: that is, (1) well-formed English, (2) a nonsense language, and (3) low-pass filtered speech producing "muffled" voices. Reducing semantic processing demands did not improve perception of emotional prosody. The TBI group were significantly less accurate than controls. Impairment was greater within the TBI group when accessing semantic memory to label the emotion of sentences, compared with simply making "same/different" judgments. Findings suggest an impairment of processing emotional prosody itself rather than semantic processing demands which leads to an over-reliance on the "what" rather than the "how" in conversational remarks. Emotional recognition accuracy was significantly related to the ability to inhibit prepotent responses, consistent with neuroanatomical research suggesting similar ventrofrontal systems subserve both functions.
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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) | 0.000 | 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 | 0.001 |
| 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 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".