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

2021-07-12 08:07:56
Alexander Ponomarchuk, Ilya Burenko, Elian Malkin, Ivan Nazarov, Vladimir Kokh, Manvel Avetisian, Leonid Zhukov
arXiv_SD
           
Abstract

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

Abstract (translated)

URL

https://arxiv.org/abs/2107.10716

PDF

https://arxiv.org/pdf/2107.10716.pdf

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