Speech Recognition for Decision Making using Machine Learning Algorithms and Techniques: A Review

In the life of human being, communication is the key element for the evolution in various fields. Information passing to the right person following exact manner helps in both commercial and delicate stage. Now we are living in a digitized world and every means of communication is only machines such as Phone calls, text messages, talking toys, vedio games, robots etc. are information communicator. Many applications have been developed to achieve the effectual communication between two sides without any disturbances. The applications act as a mediator helping in message delivery system in different forms like: coding, text, speech signals or facial expressions. The different areas of articulatory and acoustic-based speech recognition system, conversion from speech signals to text, syllable extraction and from text to synthetic speech signals, language translation, intelligent toys, human structured robots, psychological treatment and emotion recognition; where the applications have been widely used today. Through this review paper, we have observed different analytical reports of various speech feature selection methods, various clustering techniques and coding algorithms that have been applied in voice signals to attain the stated deliverables and will focus on the supervised and unsupervised techniques.