3. A system for speech recognition comprising: means for extracting prescribed feature parameters including phonetic segment units and a label sequence composed of a series of labels each having its corresponding value and representing prescribed features of phonetic segment units from input continuous speech signals; means for obtaining similarities on the phonetic segment units extracted from input continuous speech signals by executing continuous matching of the extracted phonetic segment units with a voice dictionary compiled of the phonetic segment units having prescribed phonetic meanings so that a sequence of a plurality of similarities is obtained; means for converting the similarity of phonetic segment obtained by the similarity obtaining means into a normalized similarity having a normalized standard value; means for extracting a sequence of a plurality of phonetic segment likelihoods up to a prescribed placing of order based on the normalized standard values of the normalized similarities; means for selectively scoring the values of the labels with respect to predetermined phonetic segments except for transitional phonetic segments obtained in said feature parameter extracting means by accumulating the values of the labels; plurality of transition networks formed for each word included in the input speech by use of standard phonetic segment sequence; means for passing the extracted phonetic segment likelihood sequence through said transition networks by referring to a selectively scored value obtained in said scoring means for performing word-by-word matching; and means for continuously combining results of the word-by-word matching to obtain recognition outputs of the input speech.
7. A system according to claim 3, wherein said extracting means includes an analyzing means employing mel-cepstrum as an analytic parameter in linear predictive coding analysis.