no code implementations • 11 May 2022 • Madhurananda Pahar, Marisa Klopper, Byron Reeve, Rob Warren, Grant Theron, Andreas Diacon, Thomas Niesler
This cough data include 1. 68 hours of TB coughs, 18. 54 minutes of COVID-19 coughs and 1. 69 hours of healthy coughs from 47 TB patients, 229 COVID-19 patients and 1498 healthy patients and were used to train and evaluate a CNN, LSTM and Resnet50.
no code implementations • 7 Oct 2021 • Madhurananda Pahar, Marisa Klopper, Byron Reeve, Rob Warren, Grant Theron, Andreas Diacon, Thomas Niesler
We present `wake-cough', an application of wake-word spotting to coughs using a Resnet50 and the identification of coughers using i-vectors, for the purpose of a long-term, personalised cough monitoring system.
no code implementations • 2 Apr 2021 • Madhurananda Pahar, Marisa Klopper, Robin Warren, Thomas Niesler
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.
no code implementations • 23 Mar 2021 • Madhurananda Pahar, Marisa Klopper, Byron Reeve, Grant Theron, Rob Warren, Thomas Niesler
Objective: The automatic discrimination between the coughing sounds produced by patients with tuberculosis (TB) and those produced by patients with other lung ailments.
no code implementations • 2 Dec 2020 • Madhurananda Pahar, Marisa Klopper, Robin Warren, Thomas Niesler
We present a machine learning based COVID-19 cough classifier which can discriminate COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a smartphone.