An international team made up of scientists from the universities of Granada and Eurecom (France), together with engineers from the company Biometric Vox (Murcia), have designed a method based on artificial intelligence techniques that allows the COVID-19 disease to be detected from of voice and cough recordings made to patients, so a priori it could be used in voice assistants.
To do this, the researchers have developed a technique that automatically analyzes these recordings in search of acoustic patterns that may be indicative that the person suffers from this disease.
This method is capable of detecting COVID-19 with an accuracy of around 77% by analyzing only the patient’s voice
“As we know, among other associated symptoms, patients with coronavirus have a dry cough, a feeling of shortness of breath and increased respiratory rate, so the developed method looks for alterations in the patient’s voice that may be indicative that he or she suffers from the disease”, explains José Andrés González López, professor of the Department of Signal Theory, Telematics and Communications at the UGR and one of the authors of this work.
As a result, the method proposed by the researchers is capable of detecting the COVID-19 disease with an accuracy of around 77% by analyzing only the patient’s voice, according to the results of a paper published as a preprint (not peer-reviewed) a few days ago. months by this team of Spanish and French researchers.
This method could be used in voice assistants
The advantage of this method over others currently available to detect COVID-19, such as antigen tests or PCRs, “is that our technology is completely non-invasive and instantaneous, so it could be used through an app or telephone call as a method of screening or rapid diagnosis of the disease, without the need for the patient to travel to the health center and thus put other citizens at risk”, says the UGR researcher.
The researchers also point out that this technology based on voice and cough recognition could also be applied in the future to detect or monitor other similar diseases that affect the respiratory tract, such as the flu, colds, etc.
Source: University of Granada
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