On chaotic nature of speech signals

TL;DR

This paper investigates speech signals using nonlinear dynamics, revealing their low-dimensional chaotic nature through phase portraits, correlation dimension, and Lyapunov exponent analysis.

Contribution

It demonstrates that speech signals exhibit low-dimensional chaos, providing new insights into their nonlinear dynamic properties.

Findings

Speech signals have small correlation dimension

Presence of positive Lyapunov exponent indicates chaos

Phase portraits reveal chaotic attractors in speech signals

Abstract

Various phonemes are considered in terms of nonlinear dynamics. Phase portraits of the signals in the embedded space, correlation dimension estimate and the largest Lyapunov exponent are analyzed. It is shown that the speech signals have comparatively small dimension and the positive largest Lyapunov exponent