1. A prefiltering method for use in a speech recognition system, said method comprising: receiving an acoustic description of an utterance to be recognized; storing a vocabulary of words; storing a plurality of probabilistic acoustic cluster models and using individual ones of said acoustic cluster models to represent at least a part of more than one vocabulary word; comparing at least a portion of said acoustic description from said utterance against each of said cluster models, and producing a cluster likelihood score for each cluster model against which such a comparison is made; using the cluster likelihood score produced for each cluster model to calculate a prefilter score for words represented by that cluster model; and selecting a subset of said vocabulary words to undergo a more lengthy comparison against said utterance to be recognized based on the prefilter scores associated with said vocabulary words; wherein: said acoustic description of said utterance to be recognized includes a succession of acoustic descriptions representing a sequence of sounds associated with said utterance; said cluster models each comprises a succession of probabilistic acoustic models, for modeling a sequence of sounds associated with each word represented by said cluster model; said comparing includes comparing a succession of said acoustic descriptions from the utterance to be recognized against the succession of acoustic models from each of a plurality of cluster models and producing a cluster likelihood score for each such cluster model as a result of that comparison; and said cluster models are wordstart cluster models, that is, models which only represent the initial portion of many words in said vocabulary.