mlsanityData to 7 Oct 2026

Adversarial Audio Synthesis

arXiv 1802.04208 ↗First posted 12 Feb 2018cs.SD cs.LGcited by 222

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Cited by 41 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Audio signals are sampled at high temporal resolutions, and learning to synthesize audio requires capturing structure across a range of timescales. Generative adversarial networks (GANs) have seen wide success at generating images that are both locally and globally coherent, but they have seen little application to audio generation. In this paper we introduce WaveGAN, a first attempt at applying GANs to unsupervised synthesis of raw-waveform audio. WaveGAN is capable of synthesizing one second slices of audio waveforms with global coherence, suitable for sound effect generation. Our experiments demonstrate that, without labels, WaveGAN learns to produce intelligible words when trained on a small-vocabulary speech dataset, and can also synthesize audio from other domains such as drums, bird vocalizations, and piano. We compare WaveGAN to a method which applies GANs designed for image generation on image-like audio feature representations, finding both approaches to be promising.

Key facts. Cited by 222 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Feb 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2020: 1; 2021: 57; 2022: 45; 2023: 37; 2024: 37; 2025: 36; 2026: 9.

222 papers.

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  1. 2021Efficiently Modeling Long Sequences with Structured State Spacescited by 2,424
  2. 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,339
  3. 2022Simplified State Space Layers for Sequence Modelingcited by 776
  4. 2022BigVGAN: A Universal Neural Vocoder with Large-Scale Trainingcited by 245
  5. 2021A Survey on Neural Speech Synthesiscited by 182
  6. 2024Fast Timing-Conditioned Latent Audio Diffusioncited by 178
  7. 2022It's Raw! Audio Generation with State-Space Modelscited by 171
  8. 2023Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesiscited by 150
  9. 2023Audiobox: Unified Audio Generation with Natural Language Promptscited by 120
  10. 2023Machine Learning for Synthetic Data Generation: A Reviewcited by 118
  11. 2022SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generatorscited by 96
  12. 2021Noise Estimation for Generative Diffusion Modelscited by 94
38 more
  1. 2021Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidancecited by 84
  2. 2021Deepfake Video Detection Using Convolutional Vision Transformercited by 79
  3. 2021WaveFake: A Data Set to Facilitate Audio Deepfake Detectioncited by 78
  4. 2023Diffusion Models for Time Series Applications: A Surveycited by 72
  5. 2022Synthetic Data -- what, why and how?cited by 66
  6. 2024A Survey on Diffusion Models for Time Series and Spatio-Temporal Datacited by 66
  7. 2021WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesiscited by 65
  8. 2024Analysis of Classifier-Free Guidance Weight Schedulerscited by 64
  9. 2023Multi-Source Diffusion Models for Simultaneous Music Generation and Separationcited by 63
  10. 2023SingSong: Generating musical accompaniments from singingcited by 54
  11. 2023Effectively Modeling Time Series with Simple Discrete State Spacescited by 54
  12. 2023On the Constrained Time-Series Generation Problemcited by 52
  13. 2023Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEscited by 48
  14. 2024Scaling Transformers for Low-Bitrate High-Quality Speech Codingcited by 48
  15. 2021Learning Signal-Agnostic Manifolds of Neural Fieldscited by 45
  16. 2021Non Gaussian Denoising Diffusion Modelscited by 43
  17. 2022GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networkscited by 43
  18. 2022Multi-instrument Music Synthesis with Spectrogram Diffusioncited by 42
  19. 2024Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Seriescited by 42
  20. 2022Lip to Speech Synthesis with Visual Context Attentional GANcited by 41
  21. 2022Data Augmentation techniques in time series domain: A survey and taxonomycited by 41
  22. 2024A Comprehensive Survey on Data Augmentationcited by 38
  23. 2021CRASH: Raw Audio Score-based Generative Modeling for Controllable High-resolution Drum Sound Synthesiscited by 37
  24. 2022SpecGrad: Diffusion Probabilistic Model based Neural Vocoder with Adaptive Noise Spectral Shapingcited by 37
  25. 2022Quantized GAN for Complex Music Generation from Dance Videoscited by 37
  26. 2023SoK: Privacy-Preserving Data Synthesiscited by 37
  27. 2024A Good Score Does not Lead to A Good Generative Modelcited by 36
  28. 2022Guided-TTS 2: A Diffusion Model for High-quality Adaptive Text-to-Speech with Untranscribed Datacited by 35
  29. 2024Time Series Diffusion in the Frequency Domaincited by 35
  30. 2024Time Weaver: A Conditional Time Series Generation Modelcited by 35
  31. 2021Image2Reverb: Cross-Modal Reverb Impulse Response Synthesiscited by 34
  32. 2022An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Eracited by 32
  33. 2022Extreme Generative Image Compression by Learning Text Embedding from Diffusion Modelscited by 30
  34. 2021Conditional Generative Models for Counterfactual Explanationscited by 28
  35. 2021End-to-End Video-To-Speech Synthesis using Generative Adversarial Networkscited by 27
  36. 2021Denoising Diffusion Gamma Modelscited by 27
  37. 2022Towards Building Text-To-Speech Systems for the Next Billion Userscited by 27
  38. 2021Towards Generating Real-World Time Series Datacited by 26

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