Fractal Aspects of Speech Signals: Dimension and Interpolation

摘要

The nonlinear dynamics of air flow during speech production may often result intosome small or large degree of turbulence. In this paper we quantify the geometry of speech turbulence, as reflected in the fragmentation of the time signal, by using fractal models. We describe an efficient algorithm for estimating the short-time fractal dimension of speech signals and use it for speech segmentation and sound classification. We also develop a method for fractal speech interpolation, which can be used to synthesize controlled amounts of turbulence in speech or to increase its sampling rate by preserving not its bandwidth (as classically done) but rather its fractal dimension.