mlsanityData to 14 Oct 2026

Injecting Spatial Information for Monaural Speech Enhancement via Knowledge Distillation

arXiv 2212.01012 ↗First posted 2 Dec 2022eess.AS cs.SDcited by 0

On the map: Knowledge distillation → Speech and audio distillation

Abstract (arXiv)

Monaural speech enhancement (SE) provides a versatile and cost-effective approach to SE tasks by utilizing recordings from a single microphone. However, the monaural SE lags performance behind multi-channel SE as the monaural SE methods are unable to extract spatial information from one-channel recordings, which greatly limits their application scenarios. To address this issue, we inject spatial information into the monaural SE model and propose a knowledge distillation strategy to enable the monaural SE model to learn binaural speech features from the binaural SE model, which makes monaural SE model possible to reconstruct higher intelligibility and quality enhanced speeches under low signal-to-noise ratio (SNR) conditions. Extensive experiments show that our proposed monaural SE model by injecting spatial information via knowledge distillation achieves favorable performance against other monaural SE models with fewer parameters.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Speech and audio distillation, one of 12 directions in Knowledge distillation. Builds on 7 of its 17 references that are in the map. First posted on arXiv 2 Dec 2022.

Builds on

7 of 17 references.

References · 7

  1. 2017Supervised Speech Separation Based on Deep Learning: An Overviewcited by 216
  2. 2018The Conversation: Deep Audio-Visual Speech Enhancementcited by 109
  3. 2019PHASEN: A Phase-and-Harmonics-Aware Speech Enhancement Networkcited by 51
  4. 2020Channel-Attention Dense U-Net for Multichannel Speech Enhancementcited by 19
  5. 2021Speech Enhancement Using Multi-Stage Self-Attentive Temporal Convolutional Networkscited by 4
  6. 2021Microphone Array Generalization for Multichannel Narrowband Deep Speech Enhancementcited by 3
  7. 2022Improving Dual-Microphone Speech Enhancement by Learning Cross-Channel Features with Multi-Head Attentioncited by 1

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Not cited yet.

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  1. 2024Complex-Cycle-Consistent Diffusion Model for Monaural Speech Enhancement
  2. 2026RT-SEMamba: Real-Time Speech Enhancement Mamba via Progressive Knowledge Distillation
  3. 2025DISPATCH: Distilling Selective Patches for Speech Enhancement
  4. 2025Leveraging Local and Global Knowledge Integration with Time-Frequency Calibrated Distillation for Speech Enhancement
  5. 2025Learning Robust Spatial Representations from Binaural Audio through Feature Distillation
  6. 2025Dynamic Frequency-Adaptive Knowledge Distillation for Speech Enhancement
  7. 2023Two-Step Knowledge Distillation for Tiny Speech Enhancement
  8. 2025Comparison of Knowledge Distillation Methods for Low-complexity Multi-microphone Speech Enhancement using the FT-JNF Architecture