As the battle against COVID-19 wages on around the world, scientists and researchers are turning to Artificial Intelligence (AI) to find new ways to detect, fight and treat the virus afflicting most of the planet.
Although there have been a lot of disappointing results from AI-driven clinical initiatives, one solution that now offers glimmers of hope is the use of speech-recognition technology for screening and detection of those likely to be positive for the virus.
Last October, a team of researchers from Brazilian AI giant CyberLabs Group participated in the paralinguistics challenge at Interspeech 2021, where they took home top honors for their promising new algorithm that is capable of detecting COVID-19 infections by analyzing audio clips of coughing and speech, based on early testing.
Using an advanced AI-based voice-recognition methodology, research teams analyzed several hours of audio recordings of both healthy and sick individuals to identify patterns that are consistent with COVID-19 infections. After teaching their deep-learning algorithm to recognize COVID-related sound patterns, CyberLabs was able to identify three out of four sick people correctly (75.9% of the time) when using audio recordings of their coughing, and 70.3% of the time when relying on recordings of speech.
