1. A method for detecting sentiment of a human based on an analysis of human speech, the method comprising; determining, by one or more processors, one or more time instances of glottal closure from a speech signal of the human; generating, by the one or more processors, a voice source signal based on the determined one or more time instances of glottal closure; determining, by the one or more processor, a set of relative harmonic strengths based on one or more harmonic contours of the voice source signal, wherein a relative harmonic strength (RHS) is indicative of a deviation of one or more harmonics of the voice source signal from a fundamental frequency of the voice source signal; and determining, by the one or more processors, a set of feature vectors based on the set of relative harmonic strengths, wherein the set of feature vectors is utilizable to detect the sentiment of the human.