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This mentions ICA and NMF, but in contrast to those the proposed method is supervised learning, not unsupervised. I'd suggest the authors try something like an
by cosmic_ape 8y ago
This mentions ICA and NMF, but in contrast to those the proposed method is supervised learning, not unsupervised.
I'd suggest the authors try something like an autoencoder in the waveform domain. That would be a more close analog to the ICA methods.
- cannam 8y agoI think it only mentions ICA/NMF to say that they generally aren't applied to time-domain signals, which are not non-negative and have phase as a confounding factor. Here's another intriguing (very different) recent paper on time-domain source separation: https://arxiv.org/abs/1810.12679 https://arxiv.org/abs/1810.12679
- jordipons_mtg 8y agoI'm Jordi Pons, one of the coauthors of the paper. You both are right! We basically mention ICA/sparse coding as prior work on waveform front-ends for source separation. Our method is supervised, and we did not explore the unsupervised learning approach. However, some people are doing that! Check S. Venkataramani and P. Smaragdis work! https://scholar.google.es/citations?user=hCSSNZwAAAAJ&hl=es&oi=sra https://scholar.google.es/citations?user=hCSSNZwAAAAJ&hl=es&... Although we did our best via comparing against DeepConvSep and Wave-U-Net, I agree that it would be useful to properly benchmark all that!