Disease detection using voice analysis: a review

Abstract

Disease detection using voice analysis is a vital research topic in medical engineering. It is a reliable, efficient, economic and easy to use method. It also helps to detect the diseases at its earlier stage. Voice features are extracted using some DSP techniques. These features contain information on health of voice tract and of the organs cooperating in speech production. These features represent the particular voice and may be used to discriminate voice of healthy and unhealthy persons. The time domain analysis, spectrum analysis, cepstrum analysis, glottal waveform analysis are used to extract the voice features. These features are then classified into groups using various classification techniques like vector quantisation, dynamic time wrapping, support vector machine, Gaussian mixture model and artificial neural network. This paper described all these techniques in detail.