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Sberbank has developed a neural network that recognizes COVID-19 by coughing, breathing and voice
12.01.2021 [18:58],
Vasily Shkodnik

Recently “Sberbank” never ceases to amaze. Today the company spoke about the development of an artificial intelligence laboratory. Her team was able to create a neural network capable of detecting the presence of coronavirus infection by audio data.

Image source: Lenta

For this, the analysis of spectrograms of three sound models is used – voice, respiratory and cough sounds. After receiving sound data, the information is translated into a spectrogram, which illustrates the energy of sound at different frequencies. After the received information is entered into the convolutional neural network, which then processes it and displays the result. Let us explain that the convolutional neural network differs from the usual one in that it is aimed at efficient pattern recognition. This neural network compares the entered data with a database of samples of breath and cough sounds collected from diagnosed patients in Russian clinics.

As Alexander Vedyakhin (First Deputy Chairman of the Board of Sberbank) notes in his statement, the Sber Laboratory announced its readiness to create such an algorithm in November 2021. “Of course, our model does not yet achieve the accuracy of biological PCR, which is not surprising, but it already has comparable characteristics,” says Alexander. He also draws attention to the fact that this is “not a medical diagnostic tool, but rather a personal daily checker – passing the test and getting the result takes only 60 seconds”.

In the near future, the company plans to release a special application for iPhone and smartphones on Android, which will perform sound testing for COVID-19. Also, thanks to this, the neural network will be able to recognize the disease even better.

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