114 citations · 650 across the 26 of their papers we have counts for
6 papers · 1 filter
Improving Universal Sound Separation Using Sound Classification
Efthymios Tzinis, Scott Wisdom, John R. Hershey +2
Deep learning approaches have recently achieved impressive performance on both audio source separation and sound classification. Most audio source separation approaches focus only…
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…
Bootstrapped Coordinate Search for Multidimensional Scaling
Efthymios Tzinis
In this work, a unified framework for gradient-free Multidimensional Scaling (MDS) based on Coordinate Search (CS) is proposed. This family of algorithms is an instance of General…