Study of attractor variation in the reconstructed phase space of speech signals

This paper presents a study of the attractor variation in the reconstructed phase spaces of isolated phonemes. The approach is based on recent work in timedomain signal classification using dynamical signal models, whereby a statistical distribution model is obtained from the phase space and used for maximum likelihood classification. Two sets of experiments are presented in this paper. The first uses a variable time lag phase space to examine the effect of fundamental frequency on attractor patterns. The second focuses on speaker variability through an investigation of speakerdependent phoneme classification across speaker sets of increasing size.