A nonparametric technique for speaker recognition and verification is
proposed. The proposed distance measures differ from existing distance
measures by their symmetry. These measures have been evaluated on a t
ext-dependent database, achieving a 99.6% verification rate for 200 Fr
ench speakers. In addition, it is shown that the covariance carries mo
re speaker information than the sample mean.