Application of a back-propagation neural network to isolated-word speech recognition

Abstract

The primary objective of this research is to explore how a back- propagation neural network (BNN) can be applied to isolated-word speech recognition. Simulation results show that a BNN provides an effective approach for small vocabulary systems. The recognition rate reaches 100% for a 5-word system and 94% for a 10-word system. The general techniques developed in this thesis can be further extended to other applications, such as sonar target recognition, missile seeking and tracking functions in modern weapon systems, and classification of underwater acoustic signals.