Top-down strategies in parameter selection of sinusoidal modeling of audio

Sinusoidal modeling of audio requires the model parameters to be selected by analyzing the original signal spectrum. This paper proposes two improvements in sinusoidal selection by considering how psychoacoustic masking curves can be calculated using a top-down strategy in certain situations. First, a non-iterative component selection method to be used in combination with an added residual signal is presented. Tests indicate computational gain and quality increase when the method is used with a noise-synthesized residual. Secondly, the estimation of the masking curve in binaural listening when signals are panned is considered. Tests show that knowledge of the degree of panning is beneficial when heavy panning is applied to simultaneously rendered audio object signals.