Voice verification based on nonlinear Ho-Kashyap classifier

摘要

This article presents enhancement of a linear Ho-Kashyap classifier based on kernel functions applied to speaker verification. Obtained decision function is nonlinear. Achieved verification accuracy is compared with classical techniques like Gaussian mixture models and vector quantization. Polish speech corpora ROBOT was applied as a training and testing set. Obtained results are discussed.