Beyond Model Size: Redesigning LiSenNet for embedded speech enhancement

arXiv:2609.29866 · eess.AS, cs.LG, cs.SD · Submitted 2026-09-24 · Read on arXiv

eess.AS, cs.LG, cs.SD

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• Quantization — 21× in this paper · explained in 12 episodes
• Edge AI — 3× in this paper · explained in 2 episodes
• Pruning — 3× in this paper · explained in 4 episodes
• Sparsity — 3× in this paper · explained in 4 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Causal Inference — 1× in this paper · explained in 4 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• State Management — 1× in this paper · explained in 3 episodes

Sources

• A Perceptually-Motivated Approach for Low-Complexity, Real-Time Enhancement of Fullband Speech
• Weight, Block or Unit? Exploring Sparsity Tradeoffs for Speech Enhancement on Tiny Neural Accelerators
• On the quantization of recurrent neural networks

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