Primary-ambient extraction (PAE) has been playing an important role in spatial audio analysis-synthesis. Based on the spatial features, PAE decomposes a signal into primary and ambient components, which are then rendered separately. PAE is performed in subband for complex input signals with multiple point-like sound sources. However, the performance of PAE approaches and its key influences in this case have not been well studied so far. In this paper, we conducted a study on frequency-domain PAE using principal component analysis in the case of multiple sources. We found that the partitioning of the frequency bins is very critical in PAE. Simulation results prove the superior performance of the proposed top-down adaptive partitioning method compared to the conventional partitioning methods.

This paper has been presented in ICASSP 2014.
For published version of the paper, please visit: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6854124&url=http%3...