Fractal aspects of speech signals: dimension and interpolation

The nonlinear dynamics of air flow during speech production may often result in some small or large degree of turbulence. The author quantifies the geometry of speech turbulence, as reflected in the fragmentation of the time signal, by using fractal models. He describes an efficient algorithm for estimating the short-time fractal dimension of speech segmentation and sound classification. He also develops 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 is classically done) but rather its fractal dimension.<
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