# A Summary of the ComParE COVID-19 Challenges

arXiv: https://arxiv.org/abs/2202.08981 · HTML: https://mlsanity.com/paper/2202.08981/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 23 of its 51 references that are in the map.
- First posted on arXiv 17 Feb 2022.

## Builds on (most cited first, 23 of 23)

- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Optuna: A Next-generation Hyperparameter Optimization Framework](https://mlsanity.com/paper/1907.10902/) (2019)
- [CNN Architectures for Large-Scale Audio Classification](https://mlsanity.com/paper/1609.09430/) (2016)
- [PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition](https://mlsanity.com/paper/1912.10211/) (2019)
- [Multi-task self-supervised learning for Robust Speech Recognition](https://mlsanity.com/paper/2001.09239/) (2020)
- [Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data](https://mlsanity.com/paper/2006.05919/) (2020)
- [The COUGHVID crowdsourcing dataset: A corpus for the study of large-scale cough analysis algorithms](https://mlsanity.com/paper/2009.11644/) (2020)
- [Coswara -- A Database of Breathing, Cough, and Voice Sounds for COVID-19 Diagnosis](https://mlsanity.com/paper/2005.10548/) (2020)
- [AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App](https://mlsanity.com/paper/2004.01275/) (2020)
- [The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates](https://mlsanity.com/paper/2102.13468/) (2021)
- [Cough Against COVID: Evidence of COVID-19 Signature in Cough Sounds](https://mlsanity.com/paper/2009.08790/) (2020)
- [DiCOVA Challenge: Dataset, task, and baseline system for COVID-19 diagnosis using acoustics](https://mlsanity.com/paper/2103.09148/) (2021)
- [Sounds of COVID-19: exploring realistic performance of audio-based digital testing](https://mlsanity.com/paper/2106.15523/) (2021)
- [auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks](https://mlsanity.com/paper/1712.04382/) (2017)
- [openXBOW - Introducing the Passau Open-Source Crossmodal Bag-of-Words Toolkit](https://mlsanity.com/paper/1605.06778/) (2016)
- [Detecting COVID-19 from Breathing and Coughing Sounds using Deep Neural Networks](https://mlsanity.com/paper/2012.14553/) (2020)
- [End2You -- The Imperial Toolkit for Multimodal Profiling by End-to-End Learning](https://mlsanity.com/paper/1802.01115/) (2018)
- [A Generic Deep Learning Based Cough Analysis System from Clinically Validated Samples for Point-of-Need Covid-19 Test and Severity Levels](https://mlsanity.com/paper/2111.05895/) (2021)
- [The voice of COVID-19: Acoustic correlates of infection](https://mlsanity.com/paper/2012.09478/) (2020)
- [IATos: AI-powered pre-screening tool for COVID-19 from cough audio samples](https://mlsanity.com/paper/2104.13247/) (2021)
- [Project Achoo: A Practical Model and Application for COVID-19 Detection from Recordings of Breath, Voice, and Cough](https://mlsanity.com/paper/2107.10716/) (2021)
- [Uncertainty-Aware COVID-19 Detection from Imbalanced Sound Data](https://mlsanity.com/paper/2104.02005/) (2021)
- [Evaluating the COVID-19 Identification ResNet (CIdeR) on the INTERSPEECH COVID-19 from Audio Challenges](https://mlsanity.com/paper/2107.14549/) (2021)

## Built on by (most cited first, 2 of 2)

- [WavRx: a Disease-Agnostic, Generalizable, and Privacy-Preserving Speech Health Diagnostic Model](https://mlsanity.com/paper/2406.18731/) (2024)
- [On the Impact of Voice Anonymization on Speech Diagnostic Applications: a Case Study on COVID-19 Detection](https://mlsanity.com/paper/2304.02181/) (2023)

## Abstract (arXiv)

The COVID-19 pandemic has caused massive humanitarian and economic damage. Teams of scientists from a broad range of disciplines have searched for methods to help governments and communities combat the disease. One avenue from the machine learning field which has been explored is the prospect of a digital mass test which can detect COVID-19 from infected individuals' respiratory sounds. We present a summary of the results from the INTERSPEECH 2021 Computational Paralinguistics Challenges: COVID-19 Cough, (CCS) and COVID-19 Speech, (CSS).