no code implementations • 2 Sep 2022 • Geoffrey Frost, Grant Theron, Thomas Niesler
In this work, we explore recurrent neural network architectures for tuberculosis (TB) cough classification.
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 • 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.