Acoustic and Semantic Processing of Auditory Scenes in Children with Autism Spectrum Disorders
Bibliographic record
Abstract
PURPOSE: Processing real-world sounds requires acoustic and higher-order semantic information. We tested the theory that individuals with autism spectrum disorder (ASD) show enhanced processing of acoustic features and impaired processing of semantic information. METHODS: We used a change deafness task that required detection of speech and non-speech auditory objects being replaced and a speech-in-noise task using spoken sentences that must be comprehended in the presence of background speech to examine the extent to which 7-15 year old children with ASD (n = 27) rely on acoustic and semantic information, compared to age-matched (n = 27) and IQ-matched (n = 27) groups of typically developing (TD) children. Within a larger group of 7-15 year old TD children (n = 105) we correlated IQ, ASD symptoms, and the use of acoustic and semantic information. RESULTS: Children with ASD performed worse overall at the change deafness task relative to the age-matched TD controls, but they did not differ from IQ-matched controls. All groups utilized acoustic and semantic information similarly and displayed an attentional bias towards changes that involved the human voice. Similarly, for the speech-in-noise task, age-matched-but not IQ-matched-TD controls performed better overall than the ASD group. However, all groups used semantic context to a similar degree. Among TD children, neither IQ nor the presence of ASD symptoms predict the use of acoustic or semantic information. CONCLUSION: Children with and without ASD used acoustic and semantic information similarly during auditory change deafness and speech-in-noise tasks.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".