COVID 19 Detection through voice print

We have an algorithm that detects if someone has flue like symptoms is in the vicinity, just by the tone in his speech. We are not sure yet if we can accurately differentiate between Covid type flue like symptoms and those from another cause. Regardless it should be clear that the percentage of covid infected people is higher within the set of people with flu like symptoms than in the general public. So this should still serve useful. At its broadest then it protects the user from both flu and covid . This could be implemented in an android app that is constantly on on the smart phone, even in the users pocket. The moment it hears through the earpiece someone speak it will use adapted bio metric technology to check if they have flu like symptoms and set of an alarm or vibrate if they do. That gives you the chance to avoid close contact with the indicated person, and perhaps urge them to go for more thorough testing. This application can be used by the authorities to monitor everyone's phone calls. Should they detect someone with the virus , they can use his details that he lodged with the cellular company while registering his line to track him. This does not have to be an invasion of privacy. A transformation can be made on the raw voices in the call to render the call ineligible to humans but still keep the trace of flue like symptoms before parsing it to the algorithm. The accuracy of this algorithm will ultimately depend on the quality of the dataset used and whether it is possible to differentiate between a covid flu like symptom and an ordinary flu symptom. We ask for assistance in partnering with authorities to make this possible within the respective countries that are affected. We believe that we may be able to detect the flue like symptoms from the voice of the person being tracked even before they are audible to ordinary humans and so we could possibly catch this within the window period of incubation, before the infected has had a chance to spread it.

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ABSTRACT submited

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