AI at the edge pioneer Sensory has upgraded its face and voice biometric fusion platform with features to help device and app developers build products for life post-COVID-19, the company announced. Since face masks are now a general recommendation, many biometric facial recognition systems, such as those in smartphones, are no longer performing because they cannot identity a user if the face is half covered, the company points out. Since many functions require facial recognition to operate, TrulySecure now claims it can recognize users when wearing masks and detect coughs and sneezes, without jeopardizing security. Sensory's SDK combines face and voice biometrics to operate in difficult scenarios such as background noise or facial obstruction. The two complement each other to ensure high accuracy and a seamless, touchless user experience.
In April, the team set out to collect as many recordings of coughs as they could, including those from Covid-19 patients. They established a website where people can record a series of coughs, through a cellphone or other web-enabled device. Participants also fill out a survey of symptoms they are experiencing, whether or not they have Covid-19, and whether they were diagnosed through an official test, by a doctor's assessment of their symptoms, or if they self-diagnosed. They also can note their gender, geographical location, and native language.
Researchers at the Massachusetts Institute of Technology believe they've found a way to determine if people have coronavirus based on the sound of their cough through artificial intelligence. The human ear is incapable of picking up on the acoustic variations of a coronavirus cough, but AI can, the researchers say. The technology could be a could indicator of whether or not someone should get tested for the virus, even if they don't have symptoms. A team of researchers began collecting audio recordings of coughs in April. The samples were voluntarily submitted on a website using a cell phone and laptop.
A new MIT algorithm is capable of determining, with impressive accuracy, whether or not people have COVID-19 -- just by listening to them cough. The algorithm, which the researchers trained using the sound of tens of thousands of coughs recorded over the course of the pandemic, has a 98.5 percent success rate among patients who were already diagnosed with COVID-19, BBC News reports. If they didn't have any other symptoms aside from that cough, the success rate climbed to 100 percent. It shouldn't replace a proper lab test, the BBC suggests, but it could serve as a point-of-contact test before meeting a group or attending an event. Other teams of scientists have tried to diagnose the coronavirus for just about as long as the pandemic has been raging. In March, Carnegie Mellon University scientists built a "COVID Voice Detector" app that scanned for signs of COVID-19 in the sounds of people coughing and reciting the alphabet.
It's easy to be worried when you cough these days -- is it COVID-19, or are you just clearing your throat? You might get a clearer answer soon. MIT researchers have developed AI that can recognize forced coughing from people who have COVID-19, even if they're otherwise asymptomatic. The trick was to develop a slew of neural networks that can distinguish subtle changes indicative of the novel coronavirus' effects. One neural network detects sounds associated with vocal strength.