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A Fully Convolutional Neural Network for Speech Enhancement

arXiv 1609.07132 ↗First posted 22 Sep 2016cs.LGcited by 23

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Abstract (arXiv)

In hearing aids, the presence of babble noise degrades hearing intelligibility of human speech greatly. However, removing the babble without creating artifacts in human speech is a challenging task in a low SNR environment. Here, we sought to solve the problem by finding a `mapping' between noisy speech spectra and clean speech spectra via supervised learning. Specifically, we propose using fully Convolutional Neural Networks, which consist of lesser number of parameters than fully connected networks. The proposed network, Redundant Convolutional Encoder Decoder (R-CED), demonstrates that a convolutional network can be 12 times smaller than a recurrent network and yet achieves better performance, which shows its applicability for an embedded system: the hearing aids.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Sep 2016.

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Citing papers per year: 2021: 2; 2022: 2; 2023: 4; 2024: 8; 2025: 4; 2026: 3.

23 papers.

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  1. 2024Look Once to Hear: Target Speech Hearing with Noisy Examplescited by 11
  2. 2022BirdSoundsDenoising: Deep Visual Audio Denoising for Bird Soundscited by 7
  3. 2021Noise Reduction in X-ray Photon Correlation Spectroscopy with Convolutional Neural Networks Encoder-Decoder Modelscited by 5
  4. 2023Complex Image Generation SwinTransformer Network for Audio Denoisingcited by 3
  5. 2025Linguistic Knowledge Transfer Learning for Speech Enhancementcited by 3
  6. 2021Speech Enhancement for Wake-Up-Word detection in Voice Assistantscited by 2
  7. 2023DPATD: Dual-Phase Audio Transformer for Denoisingcited by 2
  8. 2024Advancing Additive Manufacturing through Deep Learning: A Comprehensive Review of Current Progress and Future Challengescited by 2
  9. 2022Denoising Induction Motor Sounds Using an Autoencodercited by 1
  10. 2024SECP: A Speech Enhancement-Based Curation Pipeline For Scalable Acquisition Of Clean Speechcited by 1
  11. 2024Diffusion Gaussian Mixture Audio Denoisecited by 1
  12. 2024Complex Image-Generative Diffusion Transformer for Audio Denoisingcited by 1
11 more
  1. 2024Effective Noise-aware Data Simulation for Domain-adaptive Speech Enhancement Leveraging Dynamic Stochastic Perturbationcited by 1
  2. 2026Improving multichannel speech enhancement through accurate room-acoustic simulationscited by 1
  3. 2023Stock Trend Prediction: A Semantic Segmentation Approachcited by 0
  4. 2023Efficient Monaural Speech Enhancement using Spectrum Attention Fusioncited by 0
  5. 2024Effects of Dataset Sampling Rate for Noise Cancellation through Deep Learningcited by 0
  6. 2024A Dual-Branch Parallel Network for Speech Enhancement and Restorationcited by 0
  7. 2025Passive Underwater Acoustic Signal Separation based on Feature Decoupling Dual-path Networkcited by 0
  8. 2025Are Modern Speech Enhancement Systems Vulnerable to Adversarial Attacks?cited by 0
  9. 2025Unsupervised Speech Enhancement using Data-defined Priorscited by 0
  10. 2026Universal Robust Speech Adaptation for Cross-Domain Speech Recognition and Enhancementcited by 0
  11. 2026QC-GAN: A Parameter-Efficient Quaternion Conformer GAN for High-Fidelity Speech Enhancementcited by 0