NONLINEAR STATISTICS OF HUMAN SPEECH DATA
Kenneth A. Brown, KEVIN P. KNUDSON · International Journal of Bifurcation and Chaos · 2009
We study the structure of point clouds obtained as time delay embeddings of human speech signals by approximating the data sets with certain simplicial complexes and analyzing their persistent homology. Results for several different sounds are presented in embedding dimensions 3 and 4. The first Betti number allows a coarse classification of sounds into three groups: vowels, nasals and noise.