255 citations · 1.2k across the 38 of their papers we have counts for
4 papers · 2 filters
TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognition
Hakan Erdogan, Scott Wisdom, Xuankai Chang +4
We present TokenSplit, a speech separation model that acts on discrete token sequences. The model is trained on multiple tasks simultaneously: separate and transcribe each speech s…
The CHiME-7 UDASE task: Unsupervised domain adaptation for conversational speech enhancement
Simon Leglaive, Léonie Borne, Efthymios Tzinis +6
Supervised speech enhancement models are trained using artificially generated mixtures of clean speech and noise signals, which may not match real-world recording conditions at tes…
AudioSlots: A slot-centric generative model for audio separation
Pradyumna Reddy, Scott Wisdom, Klaus Greff +2
In a range of recent works, object-centric architectures have been shown to be suitable for unsupervised scene decomposition in the vision domain. Inspired by these methods we pres…
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…