Does the Use of Crowdsourced Listeners Yield Different Speech Intelligibility Results Than In-Person Listeners for Typically Developing Children?
Heather D Salvo, Tristan J Mahr, Carly Sandgren and 2 others
PMID 41610401WHAT IT FOUND
Crowdsourced listeners scored child speech as less intelligible than in-person listeners, with the largest drop for children in the mid-range of clarity.
This method underestimates performance compared to standard norms, so it should not replace clinical assessment for these patients.
Key findings
01Crowdsourced listeners produced intelligibility scores up to 7 percentage points lower than in-person listeners, even with strict quality checks.
02The discrepancy between listener types was greatest for children with mid-range intelligibility (65% to 83%).
03Using crowdsourced scores against in-person norms caused most children to drop in age percentile rank, potentially misclassifying them as impaired.
STILL TO COME
How it was doneWhat they foundWhat it means for SLPs
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What it does not show
The study used typically developing children, so the results may not generalize to patients with dysarthria or other speech disorders where error patterns are less predictable. Crowdsourced listeners did not undergo technical headphone checks, relying only on self-report, which may have introduced uncontrolled audio quality variations. The in-person listeners were a homogeneous group of university students, while crowdsourced listeners were more diverse in age and background, which may have influenced transcription accuracy independently of the listening environment.
Declared interests
The study was funded by the National Institute on Deafness and Other Communication Disorders and the National Institute of Child Health and Human Development. The authors declared no conflicts of interest.
The easy way to misread this
Do not assume that crowdsourced data is equivalent to in-person data simply because the trends look similar. The absolute scores are lower, and applying these scores to existing clinical norms will falsely classify many children as having intelligibility disorders.
Summarised by AI from the full paper, without a clinician reviewing it. Check it against the source before it changes what you do. Read it on PubMed →