| 摘要 |
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 dIJ 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'I=W1,.W2.W3 where W is a weighting factor; (2) d''I=CId'I where CI is a correction factor; (3) max p(i,j) where p(i) is the probability of occurrence of the ith phoneme; (4) min d'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. |
