Emotion through cognition: the role of cognitive limitations in shaping emotional speech identification among adults with intellectual and developmental disabilities
Bibliographic record
Abstract
Recognising emotions in speech is vital for social interactions. Adults with intellectual disabilities (AwID) often experience difficulties with emotion perception, affecting integration. However, less is known about spoken-emotion processing among AwID. The current research examines whether difficulties stem from a primary impairment in emotional processing associated with intellectual disability (ID) or a secondary impairment due to cognitive limitations associated with ID. Using an AwID-adapted version of the Test for Rating Emotions in Speech (T-RES), we assessed emotion identification in two studies. Study 1 examined spoken-emotion recognition across different levels of ID severity, focusing on lexical (semantic) and prosodic (tone of voice) cues separately. Results indicated that as ID severity increased, emotion recognition declined. Study 2 investigated the effects of task complexity on spoken-emotion perception among adults with mild ID. Findings revealed that while emotion identification was intact in simple (congruent, lexical and prosodic emotional cues match) conditions, performance deteriorated significantly in complex (incongruent, cues mismatch) conditions, suggesting a cognitive load effect. Additionally, unlike typically developed adults, AwID did not show prosodic bias. These findings support the secondary cognitive account, suggesting that spoken-emotion processing difficulties in AwID may stem from broader cognitive limitations, rather than specific impairments in emotional perception.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".