The application of Kohonen and Multilayer Perceptron Networks in the speech nonfluency analysis - Szczurowska, Izabela; Kuniszyk-Jóźkowiak, W.; Smołka, E. (Archives of Acoustics, 2006)
Paper reports the neural network tests on ability of recognition and categorising the nonfluentand fluent utterance records. 40 of 4-second fragments containing the blockade beforewords starting with stop consonants (p, b, t, d, k and g) and including from 1 to 11 stop consonantrepetitions and 40 recordings of the speech of the fluent speakers containing the samefragments were applied. Two various networks were examined. The first, Self OrganizingMap (Kohonen network), with 21 inputs and 25 neurons in output layer, was used to reducethe dimension describing the input signals. As a result of the analysis we achieved vectorsconsisting of the neurons winning in a particular time point. Those vectors were taken as aninput for the next network that was Multilayer Perceptron. Its various types: with one and twohidden layers, different kinds and time of learning were examined.