SPEECH RECOGNITION WITH STATIC AND DYNAMIC APPROACHES IN ARTIFICIAL NEURAL NETWORK

Abstract

In this research paper, speech recognition refers to the identification of utterances through the movements of lips, tongue, teeth, and other facial muscles of the speaker without using the acoustic signal. This work shows the relative benefits of both static and dynamic approaches with speech features for improved visual speech recognition system. Artificial Neural Networks (ANN) is biologically inspired computer programs that simulate the way the human brain processes information. Artificial Neural Networks (ANN) gathers their knowledge by recognizing patterns and relationships in the data, speech and learning or training them through experience of speech.