Multichannel audio separation by Direction of Arrival Based Spatial Covariance Model and Non-negative Matrix Factorization

This paper studies multichannel audio separation using non-negative matrix factorization (NMF) combined with a new model for spatial covariance matrices (SCM). The proposed model for SCMs is parameterized by source direction of arrival (DoA) and its parameters can be optimized to yield a spatially coherent solution over frequencies thus avoiding permutation ambiguity and spatial liasing. The model constrains the estimation of SCMs to a set of geometrically possible solutions. Additionally we present a method for using a priori DoA information of the sources extracted blindly from the mixture for the initialization of the parameters of the proposed model. The simulations show that the proposed algorithm exceeds the separation quality of existing spatial separation methods.

Spatial sound separation; non-negative matrix factorization; spatial covariance models; Complex-Valued NMF