1. A speech recognition method, comprising the steps of: inputting a speech signal; analyzing said input speech signal and outputting feature parameters for each of a pluraity of successive analysis frame periods of the speech represented by said speech signal; generating information of a power difference indicating whether the speech power of said speech is increasing or decreasing for each analysis frame; calculating the similarity between frames of said speech and a standard pattern stored beforehand by using said feature parameters and further feature parameters obtained from said standard pattern; correcting said calculated similarity based on said power difference information and further power difference information of said standard pattern, which is stored beforehand; and matching said speech and said standard pattern by using said corrected calculated similarity and recognizing said speech from the result of said matching.
1. A speech recognition method, comprising the steps of: inputting a speech signal; analyzing said input speech signal and outputting feature parameters for each of a pluraity of successive analysis frame periods of the speech represented by said speech signal; generating information of a power difference indicating whether the speech power of said speech is increasing or decreasing for each analysis frame; calculating the similarity between frames of said speech and a standard pattern stored beforehand by using said feature parameters and further feature parameters obtained from said standard pattern; correcting said calculated similarity based on said power difference information and further power difference information of said standard pattern, which is stored beforehand; and matching said speech and said standard pattern by using said corrected calculated similarity and recognizing said speech from the result of said matching. 4. A speech recognition method according to claim 1 wherein said feature parameters of said speech are determined utilizing autocorrelation coeffients thereof for inter-frames and sasid calculated simlarity is determined by calculating a normalized residual power from a function having variables of the auto-correlation coefficients and the standard pattern data.