1. A computer implemented method of comparing a series of observations representing unknown speech, to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, the method comprising the steps of: a) comparing two or more of the observations in one of the blocks of observations representing unknown speech, to a subset comprising one or more of the models representing known speech, to determine a likelihood of a match to each of the one or more models; b) repeating step a) for models other than those in the subset; and c) repeating steps a) and b) for a different one of the blocks, and thereby recognizing the unknown speech in terms of the known speech.
1. A computer implemented method of comparing a series of observations representing unknown speech, to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, the method comprising the steps of: a) comparing two or more of the observations in one of the blocks of observations representing unknown speech, to a subset comprising one or more of the models representing known speech, to determine a likelihood of a match to each of the one or more models; b) repeating step a) for models other than those in the subset; and c) repeating steps a) and b) for a different one of the blocks, and thereby recognizing the unknown speech in terms of the known speech. 8. The method of claim 1 wherein, step a) comprises the step of: comparing the block of observations to a lexical graph comprising a predetermined sequence of the models in the subset, wherein the sequence comprises different types of models, and the comparison is dependent on the type; and the method comprises the step of: determining the types of the models before the block is compared.