1. A method of speaker recognition that generates a likelihood that the same speaker generated a training signal and a test signal, the method comprising: generating a matched test signal and a matched training signal by performing steps for each of a plurality of frequency components, the steps comprising: adding to the strength of the frequency component in one of the test signal or training signal so that the mean strength of the frequency component of noise in the matched test signal matches the mean strength of the frequency component of noise in the matched training signal; determining the variance of the frequency component of noise in the training signal; determining the variance of the frequency component of noise in the test signal; and increasing the variance of the frequency component in one of the test signal or the training signal so that the variance of the frequency component in the noise of the matched training signal matches the variance of the frequency component in the noise of the matched test signal; creating a model based on the matched training signal; and applying the matched test signal to the model to produce the likelihood that a same speaker generated the training signal and the test signal.