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The separation of under-determined convolutive audio mixtures is generally addressed in the time-frequency domain where the sources exhibit little overlap. Most previous approaches rely on the approximation of the mixing process by complex-valued multiplication in each frequency bin. This is equivalent to assuming that the spatial covariance matrix of each source, that is the covariance of its contribution...
This article presents theoretical and experimental results about constrained non-negative matrix factorization (NMF) in a Bayesian framework, enforcing both spectral harmonicity and temporal continuity. We exhibit fast multiplicative update rules to perform the decomposition, which are then applied to perform polyphonic piano music transcription. This approach is shown to outperform other standard...
We have implemented several fast and flexible adaptive lapped orthogonal transform (LOT) schemes for underdetermined audio source separation. This is generally addressed by time-frequency masking, requiring the sources to be disjoint in the time-frequency domain. We have already shown that disjointness can be increased via adaptive dyadic LOTs. By taking inspiration from the windowing schemes used...
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