On linear and mixmax interaction models for single channel source separation

For model-based single channel source separation, one typically assumes a linear interaction model, i.e. that the mixture magnitude spectrogram is the sum of the individual source magnitude spectrograms. In the log-domain, the MIXMAX interaction model is the corresponding approximation for the linear model. Hence, one would expect similar performance for both approaches. However, in this paper we empirically show that this is not the case for vector-quantizer-based (VQ) single channel source separation. We propose factorial linear-VQ, the linear counterpart to factorial max-VQ, and compare the two methods in systematic source separation experiments. Linear-VQ performs significantly better than max-VQ for comparable code-book sizes and behaves more robustly in the presence of additive white noise. Furthermore, we compare resynthesis properties of binary and continuous time-frequency masks. While binary masks achieve a higher interference suppression, the use of continuous masks results in a consistently better signal quality.