Bark scale-based perceptual matching pursuit for improving sinusoidal audio modeling

In this paper we propose an improved sinusoidal modeling method based on perceptual matching pursuits computed in the bark scale for parametric audio coding applications. Complex exponentials compose the overcomplete dictionary for matching pursuits. The main contribution is the minimization of a perceptual distortion measure defined in the bark scale to select the optimum atom at each iteration of the pursuits. Furthermore, a psychoacoustic stopping criterion for the pursuits is presented. The proposed sinusoidal modeling method is suitable to be integrated into a parametric audio coder based on the three-part model of sines, transients and noise (STN model), as can be appreciated in experimental results. Our method provides significant advantages regarding previous works mainly because it operates in the bark scale rather than in frequency domain.