9. A computer readable medium containing executable instructions which, when executed in a processing system, causes the system to perform a method for recognizing speech comprising: receiving a speech signal into a processor; processing the received speech signal using a language model produced by integrating a finite state grammar probability and an n-gram probability with the finite state gammar probability being subordinated to the n-gram probability, wherein the language model comprises a probability that is specified by the equation ##EQU7## 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 signal.
9. A computer readable medium containing executable instructions which, when executed in a processing system, causes the system to perform a method for recognizing speech comprising: receiving a speech signal into a processor; processing the received speech signal using a language model produced by integrating a finite state grammar probability and an n-gram probability with the finite state gammar probability being subordinated to the n-gram probability, wherein the language model comprises a probability that is specified by the equation ##EQU7## 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 signal. 10. The computer readable medium of claim 9, 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.