Abstract: Disclosed is a method for obtaining a precise detected value of a similarity between voices or the like. Standard and input pattern matrices, each having a voice feature amount as a component, are prepared (S1 and S2). A reference shape having a variance different for each specified component of the pattern matrices is prepared, and positive and negative reference pattern vectors, each having a value of the reference shape as a component, are prepared. Then, while the specified component (a center of the reference shape) being made to move to each component position j1=1 to m1, j2=1 to m2 of the standard pattern matrix, a shape change between the standard and input pattern matrices is substituted for shape changes of the positive and negative reference pattern vectors. And, an amount of change in kurtosis of each reference pattern vector is numerically evaluated to obtain a shape change amount Dj1j2 (S3). Then, a value of a geometric distance between the pattern matrices is calculated from Dj1j2 (S4).

Abstract: A standard pattern vector of a normal sound, an input pattern vector of a monitored sound, a positive vector of a reference pattern, and a negative vector of the reference pattern are produced. Regarding each element, the positive vector is increased by an absolute value of a difference between the input pattern vector and the standard pattern vector if the input pattern vector is greater than the standard pattern vector, and the negative vector is increased by the absolute value if the input pattern vector is less than the standard pattern vector. A difference of a kurtosis between the positive vector and the negative vector is calculated, wherein a center of the reference shape is relatively moved to a position of each element of the positive and negative vectors respectively at every calculation. A geometric distance value between the standard pattern vector and the input pattern vector is obtained by calculating a square root of a sum of a square of each kurtosis difference.