In this paper we examine an application for phoneme segmentation of DISTBIC, a two-pass, textindependent method traditionally used for speaker segmentation. The novelty of this paper is its experimentation with use of the spectral variation function (SVF), a simple non-parametric method for phone segmentation, as a replacement for the distance measure of the first pass of DISTBIC. In doing so we aim to produce a computationally efficient method for text-independent phoneme segmentation that provides good performance. Experiments are carried out on the TIMIT database. We give a performance comparison between the SVF as previously used for segmentation, our DISTBIC-SVF algorithm, and another state-of-the-art algorithm.