Sinusoidal coding using loudness-based component selection

Abstract

Sinusoidal modelling forms the base of parametric audio coding systems, like MPEG-4 HILN, where it is combined with noise and transient models. A parametric encoder decomposes the audio signal into components that are described by appropriate models and represented by model parameters. To achieve efficient coding at very low bitrates, selection of the perceptually most relevant signal components (e.g. sinusoids) is essential, as only a limited number of component parameters can be conveyed in the bitstream. Various strategies for sinusoidal component selection have been proposed in the literature. This paper introduces a new, loudness-based strategy and tries to compare the different strategies using objective and subjective criteria.