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Riccardo Miccini

2 accepted papers

2026

From Diet to Free Lunch: Estimating Auxiliary Signal Properties using Dynamic Pruning Masks in Speech Enhancement Networks

ICASSP 2026poster

Speech Enhancement (SE) in audio devices is often supported by auxiliary modules for Voice Activity Detection (VAD), SNR estimation, or Acoustic Scene Classification to ensure robust context-aware behavior and seamless user experience. Just like SE, these tasks often employ deep learning; however, d…

Cited by 0SourcePDFScholar
2025

Scalable Speech Enhancement With Dynamic Channel Pruning

ICASSP 2025accepted

Speech Enhancement (SE) is essential for improving productivity in remote collaborative environments. Although deep learning models are highly effective at SE, their computational demands make them impractical for embedded systems. Furthermore, acoustic conditions can change significantly in terms o…

Cited by 0SourceScholar