2 papers
cs.LG2026
Knowing When to Quit: Probabilistic Early Exits for Speech Separation
Kenny Falkær Olsen, Mads Ãstergaard, Karl Ulbæk +4
In recent years, deep learning-based single-channel speech separation has improved considerably, in large part driven by increasingly compute- and parameter-efficient neural networ…
cs.SD2024
SepMamba: State-space models for speaker separation using Mamba
Thor Højhus Avenstrup, Boldizsár Elek, István László Mádi +4
Deep learning-based single-channel speaker separation has improved significantly in recent years largely due to the introduction of the transformer-based attention mechanism. Howev…