Every employed individual has been guilty of calling in sick without actually being sick. It was all fun and games, until now. Researchers from Sardar Vallabhbhai National Institute of Technology, Surat and the Rhenish University of Applied Science, Germany, have conducted a study on developing speech signal-based non-invasive diagnosis techniques in the field of biomedical signal processing. The study aimed to develop a method that can identify a person with a common cold from their speech with higher performance and fewer features. The objective of the study was to detect viral infections and similar illnesses with comparable symptoms to prevent the spread of these diseases and remotely monitor patient health.
The researchers found that the way people talk when they have a cold is different from when they don’t. They came up with three things to help figure this out: Normalized Harmonic Peak with respect to the First Harmonic Peak (NHPF), Normalized Harmonic Peak with respect to the Maximum value of Harmonic Peak (NHPM), and Successive Harmonic Peak Ratio (SHPR). NHPF and NHPM show how loud different sounds are compared to the first and loudest sound, while SHPR compares the loudness of different sounds to the ones next to them. The classifiers look at the scores for each sound and decide if it sounds like someone with a cold or not. Then, they add up all the scores for each sound and decide which one it sounds more like overall.
