A Comparative Analysis of Established Techniques and Their Applications in the Field of Gesture Detection

The combination of speech and gesture has always been a significant part of human communication. Numerous research works have been conducted on speech recognition to a point where machines can comprehend any form of natural human language. It is, however, observed that speech is only a paltry component of the expression of human thoughts and emotions. Especially, when it gives significance to the tone of the expression for the actual meaning, or, in cases where verbal communication is improbable. By expediting the data available to a machine particularly in the form of an understanding of the emotional connotation by trisecting the associated phatic communication components, improved machines can be constructed with enhanced capabilities. The study here compiles contemporary expertise on detection of gestures and its associated mannerisms while proposing modifications for inclusivity of a wider audience, with a prominent emphasis on people with communication disabilities. Furthermore, the work done in this chapter may culminate in the development of real-world applications such as determining the attentivity of students in real time, which is an indispensable asset in the post-COVID world of online interactions.