Sinusoidal component selection based on partial loudness criteria

Sinusoidal models are widely used in parametric speech and audio coding schemes. A common requirement in these applications is to select only a subset of components that provide the greatest perceptual benefit particularly at low bitrates. Usually, perceptual sinusoidal component selection algorithms make use of greedy algorithms that are computationally expensive. In this paper, we present a new algorithm that selects sinusoidal components based on the partial loudness model proposed by Moore & Glasberg. We compare the performance of the proposed algorithm in terms of perceptual benefit and computational complexity to other existing sinusoidal selection algorithms.