1. A method for the recognition of speech, of the type including the steps of storing signals representing a model of the language to be recognized, said model being of the state-transitional type, each state being uniquely identified with a phonetic unit, each state having associated with it a portion of a transition matrix which describes which states can follow it and with what probability, each state having associated with it an observational density function assigning to each set of speech feature signals that may be observed in fluent speech a likelihood of being observed in association with that state, each state having associated with it a durational density function assigning to each duration it may have a likelihood of occurrence in fluent speech; storing signals representing lexical candidates, said lexical candidates being assemblages of phonetic units of the language in association with partial phonetic information of the type found in dictionaries; sequentially converting successive time frame portions of an utterance into signals representing respective sets of acoustic feature signals representative of the portions; and accessing the stored model and stored lexical candidates to obtain signals which represent sequences of the phonetic units, including selecting the optimum ones of such sequences to produce a selection signal representing recognition of the utterance, said method being particularly characterized in that the accessing step includes assigning a phonetic unit signal and a phonetic duration signal from the stored model to one or more of said time frame portions of speech in response to one or more of said respective sets of acoustic feature signals, and maximizing independently of the stored lexical candidates the likelihoods of each phonetic unit and each phonetic duration jointly with the likelihood of observing said one or more of said respective sets of acoustic feature signals, said assigning and maximizing being performed recursively for all assignments and transitions over all time frames up to and including the present time frame; and then retracing the actual maximization results by stepping through the phonetic determinations in a strict order to produce a proposed phonetic sequence for accessing the lexical candidates, and subsequently accessing the stored lexical candidates with the proposed phonetic sequence to obtain signals representing a set of proposed lexical candidates, from which signals a final selection signal can be obtained.