Name
Title | ||
|---|---|---|
Ray-Space-Based Multichannel Nonnegative Matrix Factorization for Audio Source Separation |
Abstract | ||
|---|---|---|
Nonnegative matrix factorization (NMF) has been traditionally considered a promising approach for audio source separation. While standard NMF is only suited for single-channel mixtures, extensions to consider multi-channel data have been also proposed. Among the most popular alternatives, multichannel NMF (MNMF) and further derivations based on constrained spatial covariance models have been successfully employed to separate multi-microphone convolutive mixtures. This letter proposes a MNMF extension by considering a mixture model with Ray-Space-transformed signals, where magnitude data successfully encodes source locations as frequency-independent linear patterns. We show that the MNMF algorithm can be seamlessly adapted to consider Ray-Space-transformed data, providing competitive results with recent state-of-the-art MNMF algorithms in a number of configurations using real recordings. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/LSP.2021.3055463 | IEEE Signal Processing Letters |
Keywords | DocType | Volume |
Non -negative matrix factorization (NMF),blind source separation,array signal processing | Journal | 28 |
ISSN | Citations | PageRank |
1070-9908 | 1 | 0.35 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mirco Pezzoli | 1 | 1 | 2.71 |
| Julio José Carabias-Orti | 2 | 7 | 1.81 |
| Maximo Cobos | 3 | 162 | 20.52 |
| Fabio Antonacci | 4 | 156 | 24.08 |
| Augusto Sarti | 5 | 462 | 81.26 |