15 citations · 15 across the 3 of their papers we have counts for
3 papers
Discriminative Enhancement for Single Channel Audio Source Separation using Deep Neural Networks
Emad M. Grais, Gerard Roma, Andrew J. R. Simpson +1
The sources separated by most single channel audio source separation techniques are usually distorted and each separated source contains residual signals from the other sources. To…
Deep Remix: Remixing Musical Mixtures Using a Convolutional Deep Neural Network
Andrew J. R Simpson, Gerard Roma, Mark D. Plumbley
Audio source separation is a difficult machine learning problem and performance is measured by comparing extracted signals with the component source signals. However, if separation…
Deep Karaoke: Extracting Vocals from Musical Mixtures Using a Convolutional Deep Neural Network
Andrew J. R. Simpson, Gerard Roma, Mark D. Plumbley
Identification and extraction of singing voice from within musical mixtures is a key challenge in source separation and machine audition. Recently, deep neural networks (DNN) have…