Scalable perceptual audio representation with an adaptive three time-scale sinusoidal signal model

Abstract

This work is concerned with the development and optimization of a signal model for scalable perceptual audio coding at low bit rates. A complementary two-part signal model consisting of Sines plus Noise (SN) is described. The paper presents essentially a fundamental enhancement to the sinusoidal modeling component. The enhancement involves an audio signal scheme based on carrying out overlap-add sinusoidal modeling at three successive time scales, large, medium, and small. The sinusoidal modeling is done in an analysis-by-synthesis overlap-add manner across the three scales by using a psychoacoustically weighted matching pursuits. The sinusoidal modeling residual at the first scale is passed to the smaller scales to allow for the modeling of various signal features at appropriate resolutions. This approach greatly helps to correct the pre-echo inherent in the sinusoidal model. This improves the perceptual audio quality upon our previous work of sinusoidal modeling while using the same number of sinusoids. The most obvious application for the SN model is in scalable, high fidelity audio coding and signal modification.