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. 2022 Jan 3;3:799067. doi: 10.3389/fdgth.2021.799067

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Copyright © 2022 Chang, Jing, Ren and Schuller.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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The workflow of this study. CovNet is the proposed transfer learning framework, which includes transferring parameters and incorporating embeddings. CovNet is first applied on the Flusense as the source data, COUGHVID as the target data. Afterwards, to further validate the effectiveness of CovNet, the CovNet based pre-trained COUGHVID models are applied on two smaller Computational Paralinguistics challengE (ComParE) 2021 COVID-19 cough sub-challenge (CCS) dataset and DiCOVA 2021 Track-1 dataset.