Speech Processing using Artificial Neural Networks

A three layer perceptron network is used to classify the /i/ sound using isolated words from different speakers. A classification accuracy of 97% has been achieved. A map of phonemes is used to trace trajectories of utterances using the self-organising neural network. A crinkle factor is proposed which allows using the self-organising map to determine the inherent dimensionality of a set of points. By this technique speech data has been shown to possess an inherent dimensionality of at least four. A projection of the map and the speech data shows how the self-organising map fits the speech space.