Open Collective
Open Collective


Development of AI audio app to compare the cough of a Coronavirus (COVID-19) infected individual with the cough of an uninfected individual.


We are a team of Open Source Collaborators against COVID-19, and our goal is to release an Open-Source Artificial Intelligence (AI) Mobile App to help in the rapid-detection of COVID-19. We want to make a huge impact to relief the pain of millions of people all over the World, currently fighting or suffering the impact of this pandemic.  

We expect to help reducing the time required for diagnosis of COVID-19 by delivering a smartphone App (also accessible through Web Browsers) which can discriminate between coughs of a potentially infected patient, and a normal cough and provide some kind of metric value to inform the user. 

To reach that goal we need to start to collect cough sounds from all over the World as soon as possible, in order to train a Machine Learning model. Our rationale behind the project are: 

  • The emergence of automated cough audio analysis and research (a curated list of relevant articles is available in the JOGL project page) 
  • The advances in Deep Learning in the latest years which enables unprecedented pattern inference by successive transformation of raw data. 
  • The emerging trend on Smartphone AI applications, which could be used on-site by anyone to help the lives of millions worldwide.

Our team