Patent Document ID: 5469529
Application ID: 08124005

Base Claim:
1. A process for measuring a resemblance between a plurality of sound samples, comprising: a learning phase comprising the steps of: acoustically analyzing a reference sound sample using a p.sup.th order acoustical analysis to obtain a resultant vector signal of the reference sound sample; calculating a covariance matrix X of size p.times.p using the resultant vector signal of the reference sound sample; inverting said covariance matrix X to obtain an inverted covariance matrix X.sup.-1 ; and storing the inverted covariance matrix X.sup.31 1 in a dictionary; a test phase comprising the steps of: acoustically analyzing a test sound sample using a p.sup.th order acoustical analysis to obtain a resultant vector signal of the test sound sample; calculating a covariance matrix Y of size p.times.p using the resultant vector signal of the test sound sample; multiplying the covariance matrix Y with the inverted covariance matrix X.sup.-1 to obtain a product YX.sup.-1 ; calculating p eigenvalues .lambda.k of YX.sup.-1 ; determining a resemblance between the reference sound sample and the test sound sample using generalized sphericity functions using at least two of the following equations: ##EQU12## where a, g, and h represent respectively an arithmetic, geometric, and harmonic mean values of the eigenvalues .lambda.k, wherein the learning phase and test phase each further perform the steps of: amplifying the sound samples; filtering the amplified sound samples; and digitizing the filtered amplified sound samples.

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Claim 3:
3. A process according to claim 1, wherein the step of determining a resemblance uses the trace of the matrix YX.sup.-1 : ##EQU13## the determinant of the matrix YX.sup.-1 : ##EQU14## and the trace of the inverted matrix YX.sup.-1 : ##EQU15## without having to explicitly calculate the eigenvalues .lambda.k.