HuBERT reaches 86% accuracy and 0.93 AUC detecting COVID-19 from 893 voice samples in the Cambridge COVID-19 Sound database.
Automatic diagnosis of covid-19 disease using deep convolutional neural network with multi-feature channel from respiratory sound data: cough, voice, and breath
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Developing a Multi-variate Prediction Model For COVID-19 From Crowd-sourced Respiratory Voice Data
HuBERT reaches 86% accuracy and 0.93 AUC detecting COVID-19 from 893 voice samples in the Cambridge COVID-19 Sound database.