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Published September 24, 2020 | Version 1.0
Dataset Open

The COUGHVID crowdsourcing dataset: A corpus for the study of large-scale cough analysis algorithms

  • 1. EPFL

Description

Cough audio signal classification has been successfully used to diagnose a variety of respiratory conditions, and there has been significant interest in leveraging Machine Learning (ML) to provide widespread COVID-19 screening. The COUGHVID dataset provides over 20,000 crowdsourced cough recordings representing a wide range of subject ages, genders, geographic locations, and COVID-19 statuses. Furthermore, experienced pulmonologists labeled more than 2,000 recordings to diagnose medical abnormalities present in the coughs, thereby contributing one of the largest expert-labeled cough datasets in existence that can be used for a plethora of cough audio classification tasks. As a result, the COUGHVID dataset contributes a wealth of cough recordings for training ML models to address the world’s most urgent health crises.

Notes

For more information about the data collection, pre-processing, validation, and data structure, please refer to the following publication: https://arxiv.org/abs/2009.11644 The cough pre-processing and feature extraction code is available from the following c4science  repository: https://c4science.ch/diffusion/10770/

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Additional details

Funding

DeepHealth – Deep-Learning and HPC to Boost Biomedical Applications for Health 825111
European Commission
ML-edge: Enabling Machine-Learning-Based Health Monitoring in Edge Sensors via Architectural Customization 200020_182009
Swiss National Science Foundation