mlsanityData to 14 Oct 2026

MANNER: Multi-view Attention Network for Noise Erasure

arXiv 2203.02181 ↗First posted 4 Mar 2022eess.AS cs.SD eess.SPcited by 28

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Abstract (arXiv)

In the field of speech enhancement, time domain methods have difficulties in achieving both high performance and efficiency. Recently, dual-path models have been adopted to represent long sequential features, but they still have limited representations and poor memory efficiency. In this study, we propose Multi-view Attention Network for Noise ERasure (MANNER) consisting of a convolutional encoder-decoder with a multi-view attention block, applied to the time-domain signals. MANNER efficiently extracts three different representations from noisy speech and estimates high-quality clean speech. We evaluated MANNER on the VoiceBank-DEMAND dataset in terms of five objective speech quality metrics. Experimental results show that MANNER achieves state-of-the-art performance while efficiently processing noisy speech.

Key facts. Cited by 28 papers in the map (data through 14 Oct 2026). First posted on arXiv 4 Mar 2022.

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Citing papers per year: 2022: 5; 2023: 9; 2024: 8; 2025: 5; 2026: 1.

28 papers.

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  1. 2022StoRM: A Diffusion-based Stochastic Regeneration Model for Speech Enhancement and Dereverberationcited by 105
  2. 2023Investigating the Design Space of Diffusion Models for Speech Enhancementcited by 10
  3. 2024BSS-CFFMA: Cross-Domain Feature Fusion and Multi-Attention Speech Enhancement Network based on Self-Supervised Embeddingcited by 10
  4. 2024Mamba-SEUNet: Mamba UNet for Monaural Speech Enhancementcited by 10
  5. 2022SCP-GAN: Self-Correcting Discriminator Optimization for Training Consistency Preserving Metric GAN on Speech Enhancement Taskscited by 8
  6. 2023Diffusion-Based Speech Enhancement in Matched and Mismatched Conditions Using a Heun-Based Samplercited by 8
  7. 2022Multi-View Attention Transfer for Efficient Speech Enhancementcited by 7
  8. 2023Assessing the Generalization Gap of Learning-Based Speech Enhancement Systems in Noisy and Reverberant Environmentscited by 6
  9. 2023Disentanglement in a GAN for Unconditional Speech Synthesiscited by 4
  10. 2024MUSE: Flexible Voiceprint Receptive Fields and Multi-Path Fusion Enhanced Taylor Transformer for U-Net-based Speech Enhancementcited by 4
  11. 2025A Composite Predictive-Generative Approach to Monaural Universal Speech Enhancementcited by 4
  12. 2023Complex Image Generation SwinTransformer Network for Audio Denoisingcited by 3
16 more
  1. 2024The Effect of Training Dataset Size on Discriminative and Diffusion-Based Speech Enhancement Systemscited by 3
  2. 2025Generative Data Augmentation Challenge: Zero-Shot Speech Synthesis for Personalized Speech Enhancementcited by 3
  3. 2023A Multi-Stage Triple-Path Method for Speech Separation in Noisy and Reverberant Environmentscited by 2
  4. 2023DPATD: Dual-Phase Audio Transformer for Denoisingcited by 2
  5. 2023ROSE: A Recognition-Oriented Speech Enhancement Framework in Air Traffic Control Using Multi-Objective Learningcited by 2
  6. 2025User-guided Generative Source Separationcited by 2
  7. 2022Audio Denoising for Robust Audio Fingerprintingcited by 1
  8. 2024Diffusion Gaussian Mixture Audio Denoisecited by 1
  9. 2024Complex Image-Generative Diffusion Transformer for Audio Denoisingcited by 1
  10. 2024Heterogeneous Space Fusion and Dual-Dimension Attention: A New Paradigm for Speech Enhancementcited by 1
  11. 2024Robust Neural Processes for Noisy Datacited by 1
  12. 2022Inference and Denoise: Causal Inference-based Neural Speech Enhancementcited by 0
  13. 2023Music Augmentation and Denoising For Peak-Based Audio Fingerprintingcited by 0
  14. 2025Magnitude-Phase Dual-Path Speech Enhancement Network based on Self-Supervised Embedding and Perceptual Contrast Stretch Boostingcited by 0
  15. 2025IMSE: Efficient U-Net-based Speech Enhancement using Inception Depthwise Convolution and Amplitude-Aware Linear Attentioncited by 0
  16. 2026Dual-View Predictive Diffusion: Lightweight Speech Enhancement via Spectrogram-Image Synergycited by 0