COVID-19 detection in cough, breath and speech using deep transfer learning and bottleneck features

We present an experimental investigation into the effectiveness of transfer learning and bottleneck feature extraction in detecting COVID-19 from audio recordings of cough, breath and speech. This type of screening is non-contact, does not require specialist medical expertise or laboratory facilitie...

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Detalles Bibliográficos
Autores principales: Pahar, Madhurananda, Klopper, Marisa, Warren, Robin, Niesler, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8679499/
https://www.ncbi.nlm.nih.gov/pubmed/34954610
http://dx.doi.org/10.1016/j.compbiomed.2021.105153

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8679499/
https://www.ncbi.nlm.nih.gov/pubmed/34954610
http://dx.doi.org/10.1016/j.compbiomed.2021.105153

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