Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough

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Abstract

The COVID-19 pandemic created significant interest and demand for infection detection and monitoring solutions. In this paper, we propose a machine learning method to quickly detect COVID-19 using audio recordings made on consumer devices. The approach combines signal processing and noise removal methods with an ensemble of fine-tuned deep learning networks and enables COVID detection on coughs. We have also developed and deployed a mobile application that uses a symptoms checker together with voice, breath, and cough signals to detect COVID-19 infection. The application showed robust performance on both openly sourced datasets and the noisy data collected during beta testing by the end users.

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APA

Ponomarchuk, A., Burenko, I., Malkin, E., Nazarov, I., Kokh, V., Avetisian, M., & Zhukov, L. (2022). Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough. IEEE Journal on Selected Topics in Signal Processing, 16(2), 175–187. https://doi.org/10.1109/JSTSP.2022.3142514

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