Disclosed is a method of automated speaker identification, comprising receiving a sample speech input signal from a sample handset; deriving a cepstral covariance sample matrix from the first sample speech signal; calculating, with a distance metric, all distances between the sample matrix and one or more cepstral covariance signature matrices; determining if the smallest of the distances is below a predetermined threshold value; and wherein the distance metric is selected from d 5 ⁡ ( S , Σ ) = A + 1 H - 2 , d 6 ⁡ ( S , Σ ) = ( A + 1 H ) ⁢ ( G + 1 G ) - 4 , d 7 ⁡ ( S , Σ ) = A 2 ⁢ ⁢ H ⁢ ( G + 1 G ) - 1 , d 8 ⁡ ( S , Σ ) = ( A + 1 H ) ( G + 1 G ) - 1 , d 9 ⁡ ( S , Σ ) = A G + G H - 2 , fusion derivatives thereof, and fusion derivatives thereof with ⁢ d 1 ⁡ ( S , Σ ) = A H - 1.