Investigation of the fractal behaviour of unvoiced plosive consonants leads to interesting observations towards their classification. Experimental evidence of the fractal nature of the speech signals themselves, as well as of their derivatives and cumulative sums prompt the use of the associated fractal dimensions to form a discriminative feature set. The obtained feature set is compact in representation and easy to compute. At the same time, the discriminating capability of this feature set is seen to be promising even for speech signals sampled at 8KHz.