1. A speech recognition system including a training module for estimating mixture Gaussian densities for use in speech-unit models of the speech recognition system, said speech recognition system comprising: means for receiving an input speech signal; segmentation means for segmenting said received input speech signal into a plurality of speech units, each speech unit having a plurality of states, each state of each speech unit representing a segment of said signal, each segment including a plurality of frames; means for grouping all segments corresponding to like speech unit states for like speech units into respective sets of segments for all states of all speech units; means for estimating parameters defining a Gaussian density for each segment of each set of segments; means for merging the Gaussian densities in each set of segments into a mixture Gaussian density through successive merging of a plurality (k) of pairs of said Gaussian densities of each set of segments into (k) Gaussian densities, wherein k is an integer, wherein a plurality of mixture Gaussian densities, one for each set of segments, are created; means for estimating weights for each one of said mixture Gaussian densities, one weight for each Gaussian density in a mixture Gaussian density; and means for using the mixture Gaussian densities and the estimated weights therefore from said means for estimating weights for identifying speech units of additional input speech signals.