mlsanityData to 7 Oct 2026

Audio Super Resolution using Neural Networks

arXiv 1708.00853 ↗First posted 2 Aug 2017cs.SD cs.LGcited by 26

Not on the map. Why?

Abstract (arXiv)

We introduce a new audio processing technique that increases the sampling rate of signals such as speech or music using deep convolutional neural networks. Our model is trained on pairs of low and high-quality audio examples; at test-time, it predicts missing samples within a low-resolution signal in an interpolation process similar to image super-resolution. Our method is simple and does not involve specialized audio processing techniques; in our experiments, it outperforms baselines on standard speech and music benchmarks at upscaling ratios of 2x, 4x, and 6x. The method has practical applications in telephony, compression, and text-to-speech generation; it demonstrates the effectiveness of feed-forward convolutional architectures on an audio generation task.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Aug 2017.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 6; 2023: 5; 2024: 4; 2025: 3; 2026: 3.

26 papers.

Sort:

By area:

  1. 2023AudioLDM: Text-to-Audio Generation with Latent Diffusion Modelscited by 592
  2. 2023A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AIcited by 68
  3. 2021NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsamplingcited by 50
  4. 2022HiFi++: a Unified Framework for Bandwidth Extension and Speech Enhancementcited by 49
  5. 2022Neural Vocoder is All You Need for Speech Super-resolutioncited by 37
  6. 2022NU-Wave 2: A General Neural Audio Upsampling Model for Various Sampling Ratescited by 36
  7. 2023Miipher: A Robust Speech Restoration Model Integrating Self-Supervised Speech and Text Representationscited by 22
  8. 2022AERO: Audio Super Resolution in the Spectral Domaincited by 17
  9. 2025Audio Super-Resolution with Latent Bridge Modelscited by 13
  10. 2022Symbolic music generation conditioned on continuous-valued emotionscited by 12
  11. 2021Learning Continuous Representation of Audio for Arbitrary Scale Super Resolutioncited by 9
  12. 2024Wave-U-Mamba: An End-To-End Framework For High-Quality And Efficient Speech Super Resolutioncited by 9
14 more
  1. 2021TUNet: A Block-online Bandwidth Extension Model based on Transformers and Self-supervised Pretrainingcited by 8
  2. 2023UnDiff: Unsupervised Voice Restoration with Unconditional Diffusion Modelcited by 7
  3. 2023mdctGAN: Taming transformer-based GAN for speech super-resolution with Modified DCT spectracited by 6
  4. 2022Sound and Visual Representation Learning with Multiple Pretraining Taskscited by 5
  5. 2021SplitSR: An End-to-End Approach to Super-Resolution on Mobile Devicescited by 3
  6. 2025UniverSR: Unified and Versatile Audio Super-Resolution via Vocoder-Free Flow Matchingcited by 3
  7. 2024STAA-Net: A Sparse and Transferable Adversarial Attack for Speech Emotion Recognitioncited by 1
  8. 2024DCAE-SR: Design of a Denoising Convolutional Autoencoder for reconstructing Electrocardiograms signals at Super Resolutioncited by 1
  9. 2026LatentFlowSR: High-Fidelity Audio Super-Resolution via Noise-Robust Latent Flow Matchingcited by 1
  10. 2021Audio Spectral Enhancement: Leveraging Autoencoders for Low Latency Reconstruction of Long, Lossy Audio Sequencescited by 0
  11. 2024Speech Bandwidth Expansion Via High Fidelity Generative Adversarial Networkscited by 0
  12. 2025SUBARU: A Practical Approach to Power Saving in Hearables Using SUB-Nyquist Audio Resolution Upsamplingcited by 0
  13. 2026Discriminating real and synthetic super-resolved audio samples using embedding-based classifierscited by 0
  14. 2026On the Geometry of Music Bandwidth Extension in Latent Spaces of Audio Codecscited by 0