Speaker normalization improvement by neural network parameter optimization

In this work we investigate the use of a speaker adaptation technique, for speech recognition, based on neural network spectral mapping. Different mul tilayer perceptron neural network architectures are analyzed in order to op timize the spectral difference reduction in acoustic data of two speakers. Experiments are carried out in a telecontrol environment, used to provide v oice commands to a mobile robot, based on DTW pattern matching.