Time-frequency structured decorrelation of speech signals via nonseparable Gabor frames

We present a new approach to the linear representation of speech signals that combines desirable structure, computational efficiency and almost decorrelation. The basic principle is a statistically adapted, group-theoretical modification of the classical Gabor expansion. In contrast to traditional linear time-frequency (TF) representations which always correspond to a separable tiling of the TF plane, we suggest the use of a hexagonal (thus nonseparable) tiling whose parameters are matched to the TF correlation of the speech signal. We estimate the TF correlation via a pitch-adapted Zak-transform motivated by modeling the vocal tract as underspread system. The TF correlation determines both the optimum tiling and the optimum window.