With the emergence of Ubiquitous Computing technologies like the Internet of Things, Haptic Computing, etc., the future of Human Computer Interaction demands much more utility and capability from the systems of this day. One of the key demands for improvements would be in the area of Speech Recognition, as the interfaces of the future would expect highly accurate, spontaneous, non-constrained, language and speaker independent speech recognition implementations. This paper is an attempt to technically review and analyse the popular techniques used in Speech Recognition for various purposes (viz. Distance Time Warping, Hidden Markov Model and Artificial Neural Networks) for their advantages and disadvantages and thereby form decisive conclusions on their applicability in the light of the demands of the future described above. Our effort to formulate the disparate and complex information on speech recognition techniques into an articulated technical review and comparison shall provide the reader with key insights on the suitability of these techniques to various hypotheses for Human Computer Interaction interfaces.