β-divergence nonnegative tensor factorization with pre-trained spectral bases yields better audio source separation performance than comparable algorithms across multiple reverberant mixing conditions.
Estimation of the Spatial Information in Gaussian Model based Audio Source Separation using Weighted Spectral Bases,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.SD 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Audio Source Separation in Reverberant Environments using $\beta$-divergence based Nonnegative Factorization
β-divergence nonnegative tensor factorization with pre-trained spectral bases yields better audio source separation performance than comparable algorithms across multiple reverberant mixing conditions.