479 citations · 1.5k across the 53 of their papers we have counts for
5 papers · 1 filter
End-to-end Non-Negative Autoencoders for Sound Source Separation
Shrikant Venkataramani, Efthymios Tzinis, Paris Smaragdis
Discriminative models for source separation have recently been shown to produce impressive results. However, when operating on sources outside of the training set, these models can…
Two-Step Sound Source Separation: Training on Learned Latent Targets
Efthymios Tzinis, Shrikant Venkataramani, Zhepei Wang +2
In this paper, we propose a two-step training procedure for source separation via a deep neural network. In the first step we learn a transform (and it's inverse) to a latent space…
Continual Learning of New Sound Classes using Generative Replay
Zhepei Wang, Cem Subakan, Efthymios Tzinis +2
Continual learning consists in incrementally training a model on a sequence of datasets and testing on the union of all datasets. In this paper, we examine continual learning for t…
A Style Transfer Approach to Source Separation
Shrikant Venkataramani, Efthymios Tzinis, Paris Smaragdis
Training neural networks for source separation involves presenting a mixture recording at the input of the network and updating network parameters in order to produce an output tha…
Deep Tensor Factorization for Spatially-Aware Scene Decomposition
Jonah Casebeer, Michael Colomb, Paris Smaragdis
We propose a completely unsupervised method to understand audio scenes observed with random microphone arrangements by decomposing the scene into its constituent sources and their…