Speech recognition using multilayer perceptron

Abstract

Speech is a very powerful and fast tool for communication. That is the reason why the problem of automatic speech recognition has been fascinating computer scientists. Artificial neural networks (ANN) have been developed to model the functioning of the human brain. They are very powerful classifiers of patterns and hence can be used to recognize speech patterns. This paper discusses the work of our team on the application of ANN to the speech recognition task. We have utilized a particular class of neural networks called multilayer perceptrons (MLP) that utilize the backpropagation of error algorithm for setting of weight. After data acquisition, the speech signal is preprocessed and fed to an MLP for classification. The task is to recognize Urdu digits from zero to nine from a mono-speaker database.