Planning a fake sick leave? Beware, AI may detect your lie from your voice

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The researchers used the harmonics (vocal rhythms in human speech) to detect the people who were suffering from cold

In the latest development in the world of artificial intelligence, researchers are now working on a technology which can detect if a person has a cold or not from the tone of their voice.

AI has emerged as a breakthrough in the world of technology ever since the inception of tools like Microsoft’s new Bing, OpenAI’s ChatGPT and Google’s Bard.

New ways of using artificial intelligence are being explored by people and the emerging technology is being experimented with at a large scale.

And now reports have emerged that researchers have developed the technology in a way that is capable of detecting if a person is suffering from cold from the tone of their voice.

AI technology may prove useful in helping people detect if they have caught a cold, however, this can prove troublesome for employees who apply for fake sick leaves, lying about suffering from a cold when they are absolutely healthy.

If this technology of detecting cold becomes another revolutionary product in future, it will provide employers with the power to detect which employee is actually suffering from cold and who is faking it just by their voices over a call.

According to a report published by Business Insider, originally attributed to The Economist, the researchers working at Sardar Vallabhbhai National Institute of Technology, Surat were able to successfully analyse the vocal patterns collected from 630 people.

Out of these, the technology was able to detect that 111 were suffering from a cold. The researchers analyzed the vocal patterns to check if the technology can spot the right people who are actually affected by a cold.

The report added that harmonics (vocal rhythms in human speech) were used by the study to detect the presence of cold in people. As per the science applied in the technology, the harmonics decrease in amplitude when the person’s frequency increases.

A person, who has caught a cold, shows an irregular pattern of frequency. Depending on this phenomenon, machine-learning algorithms were utilised by researchers to analyse various individuals’ amplification differences and spot those who were suffering from a cold.

It was further reported that the people subjected to the experiment were asked to count from 1 to 40 followed and then describe the activities they did over the weekend.

They were further asked to read Aesop’s fable titled The North Wind and the Sun. The accuracy achieved by the study in detecting cold was 70 per cent.




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