mlsanityData to 14 Oct 2026

SkipConvGAN: Monaural Speech Dereverberation using Generative Adversarial Networks via Complex Time-Frequency Masking

arXiv 2211.12623 ↗First posted 22 Nov 2022eess.AS cs.LG cs.SDcited by 6

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Abstract (arXiv)

With the advancements in deep learning approaches, the performance of speech enhancing systems in the presence of background noise have shown significant improvements. However, improving the system's robustness against reverberation is still a work in progress, as reverberation tends to cause loss of formant structure due to smearing effects in time and frequency. A wide range of deep learning-based systems either enhance the magnitude response and reuse the distorted phase or enhance complex spectrogram using a complex time-frequency mask. Though these approaches have demonstrated satisfactory performance, they do not directly address the lost formant structure caused by reverberation. We believe that retrieving the formant structure can help improve the efficiency of existing systems. In this study, we propose SkipConvGAN - an extension of our prior work SkipConvNet. The proposed system's generator network tries to estimate an efficient complex time-frequency mask, while the discriminator network aids in driving the generator to restore the lost formant structure. We evaluate the performance of our proposed system on simulated and real recordings of reverberant speech from the single-channel task of the REVERB challenge corpus. The proposed system shows a consistent improvement across multiple room configurations over other deep learning-based generative adversarial frameworks.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 31 of its 58 references that are in the map. First posted on arXiv 22 Nov 2022.

Builds on

31 of 58 references.

References · 31

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19 more
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Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 3; 2024: 0; 2025: 2.

6 papers.

  1. 2023AV-RIR: Audio-Visual Room Impulse Response Estimationcited by 20
  2. 2023AdVerb: Visually Guided Audio Dereverberationcited by 15
  3. 2022Deep neural network techniques for monaural speech enhancement: state of the art analysiscited by 3
  4. 2025A Survey of Deep Learning for Complex Speech Spectrogramscited by 3
  5. 2025EDNet: A Versatile Speech Enhancement Framework with Gating Mamba Mechanism and Phase Shift-Invariant Trainingcited by 3
  6. 2023Speech Separation based on Contrastive Learning and Deep Modularizationcited by 0