2. The method of claim 1, wherein the language model is used with at least one acoustic model to perform a hypothesis search on an acoustic sequence to provide a word sequence output.
1. A method for recognizing speech comprising: receiving speech signals into a processor; processing the received speech signals using a language model produced by integrating a finite state grammar probability and an n-gram probability with the finite state grammar probability being subordinated to the n-gram probability, wherein the language model comprises a probability that is specified by the equation ##EQU4## where, w.sub.q is the word about to be predicted, H.sub.q is the admissible history for this particular word, G is the probabilistic finite state grammar, S.sub.q is the present sentence up to w.sub.q, and V is the vocabulary to which w.sub.q belongs; and generating a word sequence representative of the received speech signals.