Classification of speech data from male volunteers (normal) and patients recovering from cancer of the larynx (abnormal) is discussed. Analysis of normals and abnormals has shown that there is a significant distinction in the fundamental frequency and harmonic envelope between these groups during constant phonation of vowel sounds. This work proposes a method of deriving the Fundamental-Harmonic Normalised (FHN) spectrum from the speech data and fitting a mixture of Gaussians to model the distribution of power within the FHN spectrum. The aim of this work is to provide a set of features for subsequent classification using an Artificial Neural Network (ANN).