No More Fake Sick Leaves: AI to Find Out If People Have a Cold from the Tone of Their Voice

Researchers at Sardar Vallabhbhai National Institute of Technology in Surat have developed a technology that uses AI to find out if people have a cold from the tone of their voice.
While this technology can be useful in detecting colds, it can also help employers to know about people who often call in sick and give excuses for having a (false) cold.
While this technology can be useful in detecting colds, it can also help employers to know about people who often call in sick and give excuses for having a (false) cold. Unsplash

How many times have you applied for a fake sick leave? Leaves can be used anytime if you have them under your bucket. However, sick leaves are the way to go when asked for the 'reason' for a leave.

Sadly, there might not be more fake sick leaves if this technology becomes mainstream. Researchers at Sardar Vallabhbhai National Institute of Technology in Surat have developed a technology that uses artificial intelligence to find out if people have a cold from the tone of their voice.

While this technology can be useful in detecting colds, it can also help employers to know about people who often call in sick and give excuses for having a (false) cold.

The vocal patterns of 630 people were analyzed by the researchers at Sardar Vallabhbhai National Institute of Technology in Surat. Out of 630 people, 111 people were suffering from a cold. The study used harmonics (vocal rhythms) to check the presence of actual cold.

When frequency increases, the harmonics decrease in amplitude. Therefore, a person actually suffering from cold shows an irregular pattern of harmonics.
When frequency increases, the harmonics decrease in amplitude. Therefore, a person actually suffering from cold shows an irregular pattern of harmonics. Unsplash

When frequency increases, the harmonics decrease in amplitude. Therefore, a person actually suffering from cold shows an irregular pattern of harmonics. Researchers used machine-learning algorithms to know the amplification differences between different people. The study's accuracy in detecting cold came out to be 70%.

(Input from various media sources)

While this technology can be useful in detecting colds, it can also help employers to know about people who often call in sick and give excuses for having a (false) cold.
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