Automated COVID-19 diagnosis

This repo contains the code created by Elien Martens during IAESTE internship summer 2021, Technical University of Kosice (Slovakia).

Data

The Interspeech Computational Paralinguistics ChallengE (ComParE) 2021 proposes two challenges related to COVID-19 detection based on audio samples. Such samples represent speech and cough audio from both healthy and infected speakers. The COVID-19 Speech Sub-Challenge (CSS) offers 3.24 hours of audio recordings containing speech samples, while the COVID19 Cough Sub-Challenge (CCS) provides 1.63 hours of cough samples. The COVID-19 datasets can be obtained through The University of Cambridge.

How it works

• clone repository
• add data (see Data section), so that the structure is the following:

CovidSpeechChallenge
  |-- dist/
  		|-- lab/
		|-- wav/
  |-- features/
  |-- results/
  |-- src/
  |-- vggish/
  |-- run_experiments.sh

• run .\run_experiments.sh

Acknowledgements