  We report on cross-running the recent COVID-19 Identification ResNet (CIdeR)
on the two Interspeech 2021 COVID-19 diagnosis from cough and speech audio
challenges: ComParE and DiCOVA. CIdeR is an end-to-end deep learning neural
network originally designed to classify whether an individual is COVID-positive
or COVID-negative based on coughing and breathing audio recordings from a
published crowdsourced dataset. In the current study, we demonstrate the
potential of CIdeR at binary COVID-19 diagnosis from both the COVID-19 Cough
and Speech Sub-Challenges of INTERSPEECH 2021, ComParE and DiCOVA. CIdeR
achieves significant improvements over several baselines.
