Abstract: In a machine implemented voice recognition method, as a first step speech signals are analyzed for feature vectors which are used to compare input signals with prestored reference signals. Patterns of any suitable form are used to calculate a similarity distance measure d.sub.IJ which is tested against a threshold to select likely candidates as a first step. A second step selects the most likely candidate by using "common nature" parameters of phonemes such as relative occurrence. Five embodiments of the second step are disclosed, each using a "common nature" criteria of inference to infer (select) the most likely candidate:(1) d'.sub.I =W.sub.1,.W.sub.2.W.sub.3 where W is a weighting factor;(2) d".sub.I =C.sub.I d'.sub.I where C.sub.I is a correction factor;(3) max p(i,j) where p(i) is the probability of occurrence of the i.sup.th phoneme;(4) min d'.sub.ij as a variation of max p(i,j); and(5) N(i) is the numerical similarity of the common characteristics of the selected candidates.