8. A method for recognizing continuous speech comprising storing signals representative of the acoustic features of a set of reference words; producing a sequence of signals representative of the acoustic features of an unknown utterance; generating at least one reference word series as a candidate for said utterance responsive to the reference word and utterance feature signals; and identifying the utterance as one of said reference word series candidates; characterized in that said reference word series candidate generating step comprises; generating a signal identifying successive word position intervals for said utterance; in each identified word position interval, forming reference word series partial candidates including determining for each reference word series partial candidate of the preceding word position interval a plurality of utterance segments for each reference word beginning within a predetermined range of the utterance segment endpoint of the reference word series partial candidate of the preceding word position and corresponding to the reference word feature signals, said range overlapping the preceding word position partial candidate utterance segment; forming a signal representative of the similarity between each reference word and the corresponding determined utterance segments responsive to the reference word feature signals and said determined utterance segment feature signals; selecting reference words having a prescribed similarity to their corresponding utterance segments responsive to said similarity signals; and combining each selected reference word with the reference word series partial candidates of the preceding word position to form at least one reference word series partial candidate for said word position interval.
8. A method for recognizing continuous speech comprising storing signals representative of the acoustic features of a set of reference words; producing a sequence of signals representative of the acoustic features of an unknown utterance; generating at least one reference word series as a candidate for said utterance responsive to the reference word and utterance feature signals; and identifying the utterance as one of said reference word series candidates; characterized in that said reference word series candidate generating step comprises; generating a signal identifying successive word position intervals for said utterance; in each identified word position interval, forming reference word series partial candidates including determining for each reference word series partial candidate of the preceding word position interval a plurality of utterance segments for each reference word beginning within a predetermined range of the utterance segment endpoint of the reference word series partial candidate of the preceding word position and corresponding to the reference word feature signals, said range overlapping the preceding word position partial candidate utterance segment; forming a signal representative of the similarity between each reference word and the corresponding determined utterance segments responsive to the reference word feature signals and said determined utterance segment feature signals; selecting reference words having a prescribed similarity to their corresponding utterance segments responsive to said similarity signals; and combining each selected reference word with the reference word series partial candidates of the preceding word position to form at least one reference word series partial candidate for said word position interval. 10. A method for recognizing continuous speech according to claim 8 further characterized in that said utterance identifying step comprises generating a selection signal responsive to the endpoints of all reference word series partial candidate of a word position interval being within a predetermined range of the utterance endpoint; generating a sequence of feature signals corresponding to each reference word series candidate responsive to said selection signal; producing a signal representative of the correspondence of the utterance to each reference word series candidate responsive to the reference word series candidate feature signal sequence and said utterance acoustic feature signal sequence; and identifying the reference word series candidate having the closest correspondence to the utterance responsive to said correspondence signals.