Blind Source Separation of Real World Mixture
Independent Vector Analysis which extends the idea of ICA seems to be the most robust blind source separation algorithm. It's able to separate real world convolutive recordings into surprisingly high quality components. IVA deals with the permutation problem by modeling each source as a multivariate random variable. For more details the original IVA paper by Taesu Kim can be found here: Independent Vector Analysis: An Extension of ICA to Multivariate Components.