57 citations · 82 across the 5 of their papers we have counts for
9 papers · 1 filter
Unsupervised Multi-channel Separation and Adaptation
Cong Han, Kevin Wilson, Scott Wisdom +1
A key challenge in machine learning is to generalize from training data to an application domain of interest. This work generalizes the recently-proposed mixture invariant training…
Distance-Based Sound Separation
Katharine Patterson, Kevin Wilson, Scott Wisdom +1
We propose the novel task of distance-based sound separation, where sounds are separated based only on their distance from a single microphone. In the context of assisted listening…
End-to-End Diarization for Variable Number of Speakers with Local-Global Networks and Discriminative Speaker Embeddings
Soumi Maiti, Hakan Erdogan, Kevin Wilson +3
We present an end-to-end deep network model that performs meeting diarization from single-channel audio recordings. End-to-end diarization models have the advantage of handling spe…
Sequential Multi-Frame Neural Beamforming for Speech Separation and Enhancement
Zhong-Qiu Wang, Hakan Erdogan, Scott Wisdom +5
This work introduces sequential neural beamforming, which alternates between neural network based spectral separation and beamforming based spatial separation. Our neural networks…
Universal Sound Separation
Ilya Kavalerov, Scott Wisdom, Hakan Erdogan +4
Recent deep learning approaches have achieved impressive performance on speech enhancement and separation tasks. However, these approaches have not been investigated for separating…
Differentiable Consistency Constraints for Improved Deep Speech Enhancement
Scott Wisdom, John R. Hershey, Kevin Wilson +4
In recent years, deep networks have led to dramatic improvements in speech enhancement by framing it as a data-driven pattern recognition problem. In many modern enhancement system…