1. A recognition confidence measurement method comprising: detecting a feature vector of an input speech signal through normalization of a histogram and extracting a phoneme string from the detected feature vector of the input speech signal; obtaining information about a distance between a phoneme string of the input speech signal and a phoneme string of a predetermined vocabulary, by a predetermined phoneme confusion matrix, wherein the phoneme confusion matrix sets the distance to be decreased in proportion to the increase of the matching degree between phonemes; extracting as candidates, the phoneme string of the vocabulary that has a higher similarity which denotes a comparatively shorter distance from the speech signal, from a predetermined dictionary; estimating a lexical distance between the extracted candidates, the estimating of the lexical distance comprising selecting a pair of candidates from the extracted candidates and performing a dynamic matching of the selected pair of candidates; and determining whether the input speech signal is an in-vocabulary, based on the lexical distance, wherein the dynamic matching comprises: for each phoneme in a first candidate of the selected pair of candidates, determining as a first matching pair the phoneme in the first candidate and the corresponding phoneme in a second candidate of the selected pair of candidates and determining as a second matching pair the phoneme in the first candidate and a phoneme having an identical shape to the phoneme in the first candidate; wherein the estimating of the lexical distance further comprises: calculating a score for the pair of candidates; and estimating the lexical distance using the calculated score; wherein the calculating of the score calculates the score using the phoneme confusion matrix.