An Extension for Source Separation Techniques Avoiding Beats

The problem of separating individual sound sources from a mixture of these, known as Source Separation or Computational Auditory Scene Analysis (CASA), has become popular in the recent decades. A number of methods have emerged from the study of this problem, some of which perform very well for certain types of audio sources, e.g. speech. For separation of instruments in music, there are several shortcomings. In general when instruments play together they are not independent of each other. More specifically the time-frequency distributions of the different sources will overlap. Harmonic instruments in particular have high probability of overlapping partials. If these overlapping partials are not separated properly, the separated signals will have a different sensation of roughness, and the separation quality degrades. In this paper we present a method to separate overlapping partials in stereo signals. This method looks at the shapes of partial envelopes, and uses minimization of the difference between such shapes in order to demix overlapping partials. The method can be applied to enhance existing methods for source separation, e.g. blind source separation techniques, model based techniques, and spatial separation techniques. We also discuss other simpler methods that can work with mono signals.