Disease Prediction using Voice Analysis

Abstract

Researchers enlist Machine learning a viable solution to find vocal patterns. Our believe is voice can relay key information about personnel health and, our research proposes working towards medical diagnosis and disease risk through voice analysis. In next few years, to the advent of technology in medical science, we positively believe health conditions will be diagnosed using smartphones and another wearable technology. This paper aims to propose viable techniques to researchers that will work by recording short speech samples and analyzing for underlying diseases. For psychiatric disorders particularly, there are no blood samples and patients are often embarrassed to talk about facing mental health issues therefore, voice analysis can also be used over here to identify peculiar traits. Different countries are collecting voice analysis samples to test their tone pitch, rhythm, rate, and volume for sign of prediction like PTSD and other brain injuries and depression. Using Machine learning algorithms will help identify vocal patterns of personnel suffering diseases or any other conditions by comparing data with healthy individuals’ voice samples.