Combining advanced sinusoidal and waveform matching models for parametric audio/speech coding

This paper presents two fundamental enhancements in a hybrid audio/speech signal model based on AM/FM and transient representation: sinusoidal, transient, and noise (STN) components. The first enhancement involves a method of instantaneous sinusoidal parameters estimation using an adaptive filtering of the speech signal along its harmonic components. The second and perhaps more significant STN enhancement is concerned with transient components modelling based on the matching pursuit with frame-based psychoacoustic optimized wavelet packet dictionary. It significantly reduces the number of coefficients required to achieve a given perceptual distortion.