You are currently viewing BMC to Start Detecting Covid-19 Utilizing Voice Pattern Via Synthetic Intelligence

BMC to Start Detecting Covid-19 Utilizing Voice Pattern Via Synthetic Intelligence


Brihanmumbai Municipal Corporation (BMC) from Wednesday (August 26), onward will begin the screening of suspected coronavirus patients through artificial intelligence (AI).

According to a report published in the Hindustan Times ( a memorandum of understanding has been signed between the BMC and an Israel-based startup company, Vocalis Health. This is the first-of-its-kind initiative in the city.

Suresh Kakani, additional commissioner, BMC said, “We signed the MOU on Saturday and the study will start from Wednesday under the supervision of Dr RN Cooper Municipal General Hospital.”

The device by the startup is being used by people to collect voice samples of people across the world. The main aim of the said device is to make a diagnostic tool to identify those who are infected by the novel coronavirus.

To be able to use this, a person needs to upload their voice sample on the official website of the company.

It must be noted that this is being done as a part of a study. The collection of sample will be initiated from NESCO jumbo Covid centre, Goregaon. If the report is to be believed then more than two thousand people who are suspected of having being infected by the coronavirus and those who are at high risk of being infected will be tested with this method.

The additional commissioner also informed that this study will take a time period of two to three months.

Explaining how this mechanism will work, Dr Neelam Andrade, dean of Nair Dental Hospital and in-charge of NESCO said, “There is one voice application that can be installed on mobiles or smart laptops. The suspected patient will be asked to count a few numbers in front of the device like a breath-analyser. The voice samples will automatically get synced with the main server of the provider. Then, through artificial intelligence, the result will be procured within 30 seconds.”

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