Signal Processing Stack Exchange is a question and answer site for practitioners of the art and science of signal, image and video processing. It only takes a minute to sign up.
Sign up to join this community
I want to achieve something like this https://soundcloud.com/user7421656/sonicworx-isolate-preview .
I've researched it and a few papers mention the use of "descriptors" on the audio and use thresholds on the descriptors to determine singing sources. But before I dive in and go hard out on how these people achieved it, I wanted to make sure it's the best way to achieve an effect similar to the above link.
What's an effective method to achieving singing source separation?
The example sounds like pitch tracking combined with comb filtering. Using method like this could be implemented by "drawing" as well, as in SPEAR analysis and re-synthesis program.
If the vocal is in the middle and other instruments are not, then you can also try center channel isolation:
http://www.virtualdub.org/blog/pivot/entry.php?id=102
The methods however, sound horrible in addition to being inaccurate and full of artifacts. Better solution to the problem would be a program that could effectively guess which part of the signal belongs to the voice and which doesn't. Much more difficult for sure though.
Flexible Audio Source Separation Toolbox is available in Python, C++ and Matlab and it has demonstration files here:
