Live concert recordings consist in long multitrack audio samples with significant interferences between channels. For audio engineering purposes, it is desirable to attenuate those interferences. Recently, we proposed an algorithm to this end based on Non-negative Matrix Factorization, that iteratively estimate the clean power spectral densities of the sources and the strength of each in each microphone signal, encoded in an interference matrix. Although it behaves well, this method is too demanding computationally for full-length concerts lasting more than one hour. In this paper, we show how random projections of the data can be leveraged for effective estimation of the parameters. Interference reduction with these ideas can be achieved on full-length live multi-track recordings in an acceptable time and could be used by sound engineers. We demonstrate the efficiency of this approach on real full-length live recordings from the Montreux Jazz Festival and also provide an implementation of the method.