<p>A set of "m" feature parameters is generated every frame from reference speech which is spoken by at least one speaker and which represents recognition-object words, where "m" denotes a preset integer. A set of "n" types of standard patterns is previously generated on the basis of speech data of a plurality of speakers, where "n" denotes a preset integer. Matching between the feature parameters of the reference speech and each of the standard patterns is executed to generate a vector of "n" reference similarities between the feature parameters of the reference speech and each of the standard patterns every frame. The reference similarity vectors of respective frames are arranged into temporal sequences corresponding to the recognition-object words respectively. The reference similarity vector sequences are previously registered as dictionary similarity vector sequences. Input speech to be recognized is analyzed to generate "m" feature parameters from the input speech. Matching between the feature parameters of the input speech and the standard patterns is executed to generate a vector of "n" input-speech similarities between the feature parameters of the input speech and the standard patterns every frame. The input-speech similarity vectors of respective frames are arranged into a temporal sequence. The input-speech similarity vector sequence is collated with the dictionary similarity vector sequences to recognize the input speech. <IMAGE></p>
