activity
20202022
most citedSounds of COVID-19: exploring realistic performance of audio-based digital testing

5 citations · 7 across the 2 of their papers we have counts for

collaborators

5 papers

cs.SD2022

A Summary of the ComParE COVID-19 Challenges

Harry Coppock, Alican Akman, Christian Bergler +17

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 c…

cs.SD20215 cited

Sounds of COVID-19: exploring realistic performance of audio-based digital testing

Jing Han, Tong Xia, Dimitris Spathis +9

Researchers have been battling with the question of how we can identify Coronavirus disease (COVID-19) cases efficiently, affordably and at scale. Recent work has shown how audio b…

eess.AS20212 cited

The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates

Björn W. Schuller, Anton Batliner, Christian Bergler +21

The INTERSPEECH 2021 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the CO…

cs.SD2021

Exploring Automatic COVID-19 Diagnosis via voice and symptoms from Crowdsourced Data

Jing Han, Chloë Brown, Jagmohan Chauhan +6

The development of fast and accurate screening tools, which could facilitate testing and prevent more costly clinical tests, is key to the current pandemic of COVID-19. In this con…

cs.SD2020

Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data

Chloë Brown, Jagmohan Chauhan, Andreas Grammenos +6

Audio signals generated by the human body (e.g., sighs, breathing, heart, digestion, vibration sounds) have routinely been used by clinicians as indicators to diagnose disease or a…