Hybrid representations for audiophonic signal encoding

In this paper, we discuss a new approach for signal models in the context of audio signal encoding. The method is based upon hybrid models featuring simultaneously transient, tonal and stochastic components in the signal. Contrary to several existing approaches, our method does not rely on any prior segmentation of the signal. The three components are estimated and encoded using a strategy very much in the spirit of transform coding. While the details of the method described here are tailored to audio signals, the general strategy should also apply to other types of signals exhibiting significantly different features, for example images.