Modeling speech-interfering noise with applied chaos theory

One of the primary difficulties involved with speech recognition is dealing with sounds other than speech that may occur while a person is speaking. There have been many techniques that attempt to deal with background "noise." Many of these make use of some type of stochastic model to decrease the effect of the interfering signal. This paper, however, investigates the possibility of a new technique involving nonlinear chaos theory. The idea of chaos has been of growing interest in physics and has begun to enter the world of signal processing with some good results. In a simple sense, a chaotic signal is one that appears random but has some underlying, nearly deterministic structure. This paper considers using some of the knowledge from chaos theory in modeling background "noise" that may interfere with a recognizer or other speech system.