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Author

Simon Leglaive

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#artificial intelligence Preprint Sep 2026

Masked Autoregressive Speech Enhancement with Continuous Neural Audio Codec Representations

This work proposes masked autoregressive SE (MARSE), a method for SE based on iterative decoding of masked clean speech frames using continuous NAC representations of speech, which enables a flexible trade-off between SE performance and computational cost.

Yoto Fujita, Simon Leglaive, Laurent Girin · 0 citations
#artificial intelligence Preprint Sep 2026

Test-time adaptation for speech enhancement with an autoregressive speech prior

Test-time adaptation (TTA) offers a promising direction for improving speech enhancement models under mismatched acoustic conditions, without requiring access to labeled target data. In this work, we propose a single-utterance TTA method that regularizes a pretrained speech enhancement model using an autoregressive pri...

S. Kammoun, Simon Leglaive, Xavier Alameda-Pineda et al. · 1 citation

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