255 citations · 1.2k across the 38 of their papers we have counts for
4 papers · 2 filters
Adapting Speech Separation to Real-World Meetings Using Mixture Invariant Training
Aswin Sivaraman, Scott Wisdom, Hakan Erdogan +1
The recently-proposed mixture invariant training (MixIT) is an unsupervised method for training single-channel sound separation models in the sense that it does not require ground-…
Improving On-Screen Sound Separation for Open-Domain Videos with Audio-Visual Self-Attention
Efthymios Tzinis, Scott Wisdom, Tal Remez +1
We introduce a state-of-the-art audio-visual on-screen sound separation system which is capable of learning to separate sounds and associate them with on-screen objects by looking…
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…
Self-Supervised Learning from Automatically Separated Sound Scenes
Eduardo Fonseca, Aren Jansen, Daniel P. W. Ellis +7
Real-world sound scenes consist of time-varying collections of sound sources, each generating characteristic sound events that are mixed together in audio recordings. The associati…