Speech processing by hierarchical segment classification

A neural network for speech processing is presented. Its complex architecture, incorporating selforganizing feature maps, allows the construction of a hierarchy of layers, where each layer operates on a larger time scale and deals with higher units of speech, like phonemes, syllables, word parts and so on. Tasks the network has to deal with include representation of speech, segmentation of the speech signal and classifying segments.