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Classifying Autism From Crowdsourced Semistructured Speech Recordings: Machine Learning Model Comparison Study

Classifying Autism From Crowdsourced Semistructured Speech Recordings: Machine Learning Model Comparison Study

Cho et al [17] developed models that achieved 76% accuracy on a dataset of recorded interviews between children and unfamiliar adults, trained on data recorded at a consistent location using a specialized biosensor device with 4 directional microphones. Similarly, Li et al [18] achieved high accuracies when training on speech data recorded with multiple wireless microphones, providing high purity recordings at a central recording location (a hospital).

Nathan A Chi, Peter Washington, Aaron Kline, Arman Husic, Cathy Hou, Chloe He, Kaitlyn Dunlap, Dennis P Wall

JMIR Pediatr Parent 2022;5(2):e35406