mlsanityData to 14 Oct 2026

Complex Image Generation SwinTransformer Network for Audio Denoising

arXiv 2310.16109 ↗First posted 24 Oct 2023cs.SD cs.CV eess.AScited by 3

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Abstract (arXiv)

Achieving high-performance audio denoising is still a challenging task in real-world applications. Existing time-frequency methods often ignore the quality of generated frequency domain images. This paper converts the audio denoising problem into an image generation task. We first develop a complex image generation SwinTransformer network to capture more information from the complex Fourier domain. We then impose structure similarity and detailed loss functions to generate high-quality images and develop an SDR loss to minimize the difference between denoised and clean audios. Extensive experiments on two benchmark datasets demonstrate that our proposed model is better than state-of-the-art methods.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 22 of its 36 references that are in the map. First posted on arXiv 24 Oct 2023.

Builds on

22 of 36 references.

References · 22

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
  3. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,223
  4. 2015SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentationcited by 1,487
  5. 2021Segmenter: Transformer for Semantic Segmentationcited by 855
  6. 2021MetricGAN+: An Improved Version of MetricGAN for Speech Enhancementcited by 114
  7. 2021Mixed Transformer U-Net For Medical Image Segmentationcited by 95
  8. 2019Phase-aware Speech Enhancement with Deep Complex U-Netcited by 73
  9. 2019PHASEN: A Phase-and-Harmonics-Aware Speech Enhancement Networkcited by 51
  10. 2021TSTNN: Two-stage Transformer based Neural Network for Speech Enhancement in the Time Domaincited by 36
  11. 2022MANNER: Multi-view Attention Network for Noise Erasurecited by 28
  12. 2016A Fully Convolutional Neural Network for Speech Enhancementcited by 23
10 more
  1. 2018Convolutional-Recurrent Neural Networks for Speech Enhancementcited by 17
  2. 2021Speech Denoising Without Clean Training Data: A Noise2Noise Approachcited by 17
  3. 2022A Two-Stage U-Net for High-Fidelity Denoising of Historical Recordingscited by 17
  4. 2021S-DCCRN: Super Wide Band DCCRN with learnable complex feature for speech enhancementcited by 14
  5. 2022Speech Denoising in the Waveform Domain with Self-Attentioncited by 13
  6. 2021Speech enhancement with weakly labelled data from AudioSetcited by 9
  7. 2022BirdSoundsDenoising: Deep Visual Audio Denoising for Bird Soundscited by 7
  8. 2020DCCRGAN: Deep Complex Convolution Recurrent Generator Adversarial Network for Speech Enhancementcited by 4
  9. 2018Deep Denoising for Hearing Aid Applicationscited by 3
  10. 2016Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognitioncited by 1

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 2.

3 papers.

  1. 2023DPATD: Dual-Phase Audio Transformer for Denoisingcited by 2
  2. 2024Diffusion Gaussian Mixture Audio Denoisecited by 1
  3. 2024Complex Image-Generative Diffusion Transformer for Audio Denoisingcited by 1