Abstract
The article discusses an application of Kullback-Leibler divergence to the recognition of speech signals and suggests three algorithms implementing this divergence criterion: correlation algorithm, spectral algorithm and filter algorithm. Discussion covers an original approach to the problem of speech variability and is illustrated with results of experimental speech signal modeling. The article gives a number of recommendations on the choice of appropriate model parameters and provides a comparison to some other methods of speech recognition.