Author

W. Kleijn

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Preprint Sep 2026

Unsupervised Speech Enhancement via Drifting

This paper addresses unsupervised speech enhancement in the unpaired setting using drifting methods, where training relies on separate collections of degraded and clean audio without corresponding pairs. While recent drifting approaches enable unpaired training, they do so at a heavy cost: because the objective optimiz...

Diego Caviedes-Nozal, Liang Xu, R. Olsson et al. · 0 citations

#artificial intelligence Preprint Sep 2026

DriftSE: Speech Enhancement with Generative Drifting

This work introduces dual-latent drifting, performing parallel drifting in both semantic and acoustic latents to simultaneously preserve phonetic intelligibility and acoustic fidelity and demonstrates that DriftSE enables fully unpaired training by aligning latent distributions rather than exact point-wise targets.

Liang Xu, Diego Caviedes-Nozal, W. Kleijn et al. · 1 citation