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Found 5 papers, 1 papers with code
Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data
This work opens the door to further investigation of how automatically analysed respiratory patterns could be used as pre-screening signals to aid COVID-19 diagnosis.
The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates
The INTERSPEECH 2021 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the COVID-19 Cough and COVID-19 Speech Sub-Challenges, a binary classification on COVID-19 infection has to be made based on coughing sounds and speech; in the Escalation SubChallenge, a three-way assessment of the level of escalation in a dialogue is featured; and in the Primates Sub-Challenge, four species vs background need to be classified.
Sounds of COVID-19: exploring realistic performance of audio-based digital testing
In this paper, we explore the realistic performance of audio-based digital testing of COVID-19.
Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validation
Recent work has shown the potential of using audio data (eg, cough, breathing, and voice) in the screening for COVID-19.
A Summary of the ComParE COVID-19 Challenges
The COVID-19 pandemic has caused massive humanitarian and economic damage.
